Engineering Structures Jobs No Experience Jobs in Berkeley, CA

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keep up with industry trends in recommendation systems
  
• Leverage LLMs to enhance content understanding
  

What we're looking for:

• 
  
• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• Degree in computer science, statistics, or related field; or equivalent experience
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
  
• Nice to have:
  
  • 
    
  • M.S. or PhD in Machine Learning or related areas
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  • Background in computational advertising
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-HYBRID

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keeping up with industry trends in recommendation systems
  

What we're looking for:

• 
  
• 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Degree in computer science, machine learning, statistics, or related field
  
• Nice to have:
  
  • 
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-SA1

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keeping up with industry trends in recommendation systems
  

What we're looking for:

• 
  
• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Degree in computer science, machine learning, statistics, or related field
  
• Nice to have:
  
  • 
    
  • M.S. or PhD in Machine Learning or related areas
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-SA1

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

Open date: June 14, 2025

Most recent review date: Tuesday, Jul 29, 2025 at 11:59pm (Pacific Time)

Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Tuesday, Aug 25, 2026 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

The College of Chemistry at the University of California, Berkeley is generating an applicant pool of qualified lecturers to teach graduate courses on the Berkeley campus for the Master of Molecular Science and Software Engineering (MSSE) Program should an opening arise. We are seeking dynamic lecturers with a commitment to graduate education in computational science, data science, and software engineering to lead multiple courses each year. Disciplines where we are seeking instructors include:

• 
  
• Computational Chemistry
  
• Computational Quantum Chemistry
  
• Scientific Computing
  
• Machine Learning/Deep Learning
  
• Structural Bioinformatics
  
• High Performance Computing
  
• Complex mathematical modeling and simulations
  
• Leadership, management, and entrepreneurship
  

The MSSE Program is a unique program that is designed to formally train scientists, engineers, and computer scientists in computational and data science, and to provide them with the tools, software engineering practices, leadership, management, and entrepreneurial skills needed to create or lead science- or engineering-based enterprises. While the degree focuses on the molecular sciences, its content is suitable for any student pursuing software engineering or data science roles in other science-based industries, or in other areas that require advanced machine learning, complex mathematical modeling and simulations, or high-performance computing.

General Duties:

Classroom teaching and preparation, managing and mentoring graders and/or graduate student instructors (teaching assistants), holding office hours, assigning grades, advising students, preparing course materials (e.g., syllabus), and using Cal's electronic resources for course management.

The MSSE Program seeks candidates who can support the success of all students through inclusive curriculum, classroom environment, and pedagogy.

Program:

Contract for the Lecturers Unit (IX) between the University of California and the American Federation of Teachers:

Advanced degree or enrolled in an advanced degree program.

Advanced degree.

• 
  
• A Ph.D., or equivalent international degree, in an area related to computational science, data science, and/or software engineering
  
• Prior teaching and/or work experience in computational science, data science, and/or software engineering
  
• Leadership, management, and entrepreneurial skills in STEM fields
  
• Existing authorization to work in the U.S.
  
• Proficient in C++ and Python programming languages
  

• Curriculum Vitae - Your most recently updated C.V.

  
  

• Cover Letter (Optional)

  
  

• Statement of Teaching

  
  

• 3-5 required (contact information only)

Help contact:

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• 
  
• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  
• UC Sexual Violence and Sexual Harassment Policy
  
• UC Anti-Discrimination Policy
  
• APM - 035: Affirmative Action and Nondiscrimination in Employment
  

Open date: June 14, 2025

Most recent review date: Saturday, Jun 28, 2025 at 11:59pm (Pacific Time)

Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Thursday, Oct 1, 2026 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

The College of Chemistry at the University of California, Berkeley invites applications for a pool of temporary instructors to assist in teaching graduate courses online for the Master of Molecular Science and Software Engineering (MSSE) Program, should an opening arise. Candidates will support the primary instructors assigned to the courses.

Disciplines where we are seeking lecturers in lieu of GSIs include:

• 
  
• Computational Chemistry
  
• Scientific Computing
  
• Bioinformatics
  
• Machine Learning/Deep Learning
  
• High Performance Computing
  
• Complex mathematical modeling and simulations
  
• Computational Quantum Chemistry
  
• Leadership, management, and entrepreneurship in a computational science company or organization
  

General Duties

Duties include assisting or leading lectures, leading or assisting in labs or discussions, and other activities customarily related to instructional assignments (i.e., grading assignments, submitting/maintaining student records, responding to student questions, tutoring students, holding regular office hours, course material preparation, attending relevant meetings, orientations, etc.).

The MSSE Program seeks candidates who can support the success of all students through inclusive curriculum, classroom environment, and pedagogy.

Program:

Union contract: resources/employment-policies-contracts/bargaining-units/non-senate-instructional/contract/

A bachelor's degree, or equivalent international degree, or enrolled in a bachelor's degree, or equivalent international degree, program.

A bachelor's degree, or equivalent international degree, and authorization to work in the U.S.

• 
  
• A master's degree, or equivalent international degree, in an area related to computational science, computational chemistry, bioinformatics, data science, high performance computing, mathematical modeling and simulations, or software engineering
  
• Proficiency in C++ and Python programming languages
  

• Curriculum Vitae - Your most recently updated C.V.

  
  

• Cover Letter (Optional)

  
  

• Statement of Teaching (Optional)

  
  

Help contact:

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• 
  
• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  
• UC Sexual Violence and Sexual Harassment Policy
  
• UC Anti-Discrimination Policy
  
• APM - 035: Affirmative Action and Nondiscrimination in Employment
  

Talent Acquisition Manager – AI Infrastructure & Engineering

San Francisco, California

Hybrid Working

We are expanding our global team and launching a new office in San Francisco.

WNTD is looking for an experienced Talent Acquisition Manager to join our Talent Solutions team and support the continued growth of AI infrastructure and accelerated compute platforms across North America.

This role will support one of the most significant AI infrastructure expansion programmes currently underway, focused on building next generation platforms powered by NVIDIA accelerated compute.

You will work closely with senior technical leaders to attract and hire talent across the full infrastructure stack including software engineering, AI platforms, GPU environments and large scale compute infrastructure.

This is a delivery focused role supporting high growth engineering programmes across AI infrastructure and cloud platforms.

The Role

You will lead hiring across multiple engineering disciplines spanning software engineering, AI infrastructure platforms and high performance compute environments.

Working closely with technical leadership and programme stakeholders, you will build pipelines of high quality candidates and manage fast moving hiring plans across several technical workstreams.

Key Responsibilities

• Build and manage talent pipelines across software engineering, AI infrastructure and GPU compute environments

• Proactively source talent across the United States through mapping, referrals and direct outreach

• Screen candidates for technical capability, experience and long term fit

• Partner with engineering leaders to define hiring priorities and role requirements

• Maintain clear tracking of hiring pipelines and delivery progress

• Support wider Talent Solutions activity during peak delivery phases

• Ensure a professional and consistent candidate experience

• Champion fair and inclusive hiring practices

Key Experience

• Proven experience hiring across complex engineering environments

• Strong track record building pipelines across software and infrastructure roles

• Comfortable engaging with technical stakeholders and discussing engineering topics

• Excellent communication and stakeholder management skills

• Strong organisation with the ability to manage multiple roles simultaneously

What We Offer

• Competitive salary and benefits

• Opportunity to support one of the fastest growing AI infrastructure build programmes globally

• Growth within a high performing delivery focused team

• Hybrid working model

• A collaborative culture that values ownership, pace and problem solving

Additional Requirements

• Ability to commute to the San Francisco office

• No visa sponsorship available

• Hybrid working model

Fractal is a strategic AI partner to Fortune 500 companies, with a bold vision: to power every human decision in the enterprise. We believe the future belongs to organizations that combine human imagination with intelligent systems—and Fractalites are the ones building that future. As we scale our Technology, Media & Telecom (TMT) practice in the United States, we are looking for a senior, client-facing Head of Engineering to shape and deliver world-class Data & AI platforms for leading Technology, Media & Telecom organizations.

This is not a back-office engineering role. This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom.

Learn more at Fractal | Intelligence for Imagination.

Note: This position is not eligible for Immigration Sponsorship at this time.

About the Role

This is a four-axis leadership role requiring technical depth, executive presence, team leadership, and embedded delivery. You'll work directly with top technical and functional leaders at some of the largest TMT companies in the world.

As Head of Engineering for Fractal's Technology, Media & Telecom (TMT) vertical, you will personally shape the architecture of mission-critical AIML platforms, often in first-party tech stack, and develop/drive the team of ICs who bring them to life.

Responsibilities

Some engagements will look like a traditional advisory model. Others will look a lot more like Forward Deployed Engineering: your team embedded inside a client's engineering org, working within their first-party tech stack, shipping production code alongside their engineers, and earning influence through technical credibility, not org chart position.

You will need to be in the room when the technology roadmap needs to change. When a business pivot, a new regulation, or a technology shift forces a rethink mid-execution, you are the person who picks up the marker, walks to the whiteboard, and redraws the architecture in real time, credibly, for the CTO, and Principal Engineering leaders simultaneously.

Technical Depth (Hands-On Architecture)

• Own AI/Data platform architecture decisions — from Lakehouse design and real-time streaming to MLOps, LLMOps, and AgentOps pipelines in production
• Serve as the technical authority for Fractal's TMT engineering practice — defining standards, reviewing design, and holding the bar on reliability, scalability, and security
• Translate ambiguous business problems into concrete, buildable platform architectures — and stay close enough to execution to know when something is not working
• Drive the industrialization of GenAI: moving clients from proof-of-concept to enterprise-grade, governed, and observable AI systems

Executive Presence & Live Architectural Thinking

• Command the room with senior client leadership — CIOs, CTOs, CDOs, and their direct reports - as a peer, not a vendor
• Whiteboard new architectural directions on the spot: when a business pivot, acquisition, regulatory shift, or technology breakthrough forces a mid-execution rethink, you synthesize it into a credible, buildable path forward live, in the room, without needing a week to prepare a deck
• Translate between two worlds simultaneously: make the architecture legible to a CFO and rigorous enough to satisfy a principal engineer in the same session
• Shape client roadmaps at the strategic level; identifying where the current plan is under-ambitious, over-engineered, or misaligned with emerging AI capabilities, and steering accordingly
• Represent Fractal at the highest level of client relationship

Team Leadership (Building & Driving Senior ICs)

• Develop and lead a high-performing group of individual contributors. principally senior and staff engineers, ML engineers, and data platform engineers
• Create the engineering culture: rigorous delivery standards, architectural thinking, and a bias toward elegant, production-grade solutions over quick fixes
• Build leadership depth within the team, identifying principals who can own programs and grow into broader roles
• Partner across Fractal's global AI and engineering Capability functions to staff programs strategically and raise capability across the TMT practice

Forward-Deployed & Embedded Delivery

• Lead and run FDE-style engagements where your team operates inside the client's engineering environment
• Navigate and deliver within client-owned, first-party technology stacks: proprietary data platforms, internal ML infrastructure, custom orchestration systems, and bespoke toolchains that do not appear in any industry survey
• Adapt quickly to non-standard environments, understanding a client's internal platform deeply enough to extend it, integrate into it, and earn the trust of their engineering staff
• Balance the tension between what Fractal does best and what the client's stack demands, knowing when to bring pattern, when to adapt, and when to advocate for a better path
• Set the standards for how Fractal operates in deeply embedded engagements: how we onboard, document, transfer knowledge, and leave clients stronger than we found them

Candidate Profile

Technical Qualifications

TMT clients bring genuinely hard problems on both open and proprietary infrastructure. Expect to architect and oversee:

• GenAI systems: RAG architectures, LLM fine-tuning pipelines, agentic workflow orchestration, and LLMOps observability
• AI-powered products: personalization engines, churn prediction, content recommendation, and network fault detection
• Client-proprietary ML infrastructure: internal feature stores, custom model serving layers, bespoke experiment tracking systems, and first-party orchestration frameworks
• Cloud-native infrastructure across AWS, Azure, and GCP with enterprise-grade governance, security, and compliance baked in
• Real-time and event driven data pipelines (e.g. network telemetry)
• Modern Lakehouse platforms (Databricks, Snowflake, Delta Lake, Iceberg) at petabyte scale and proprietary data platform equivalents at leading tech-forward TMT organizations

Non-technical Qualifications

We are particularly interested in leaders from environments where engineering rigor, client accountability, executive presence, and AI depth all coexist including Forward Deployed Engineering, elite data/ML platform teams, and senior hyperscaler architecture practices.

• 15–20 years of experience spanning AI/data engineering and technical leadership with clear evidence of owning architecture at scale
• Deep hands-on experience deploying AI/ML/GenAI systems in production, in addition to advising on them
• Demonstrated executive presence: you have walked into a CTO or CDO review, redrawn the architecture based on new constraints, and left the room with alignment
• The ability to whiteboard fluently under pressure, synthesizing a team's in-flight work with a new business direction, making it rigorous enough for engineers and clear enough for executives, on the spot and without a rehearsal
• Experience operating within client-owned or non-standard technology stacks - you have learned a proprietary system, earned trust from skeptical internal engineers, and delivered production-grade results inside someone else's infrastructure
• A track record of leading senior engineers and building high-performance ML/engineering teams, including hiring, coaching, and developing principal-level ICs
• Direct executive engagement experience - you have influenced CIO/CTO/CDO decisions and can hold your own in a room with technical and non-technical stakeholders at once
• Strong cloud-native fluency across one or more hyperscalers, with genuine depth in data platform patterns (streaming, batch, Lakehouse, governance)

Strong Preferences

• Experience in TMT vertical — hi-tech, telco, media platforms, streaming infrastructure, ad tech, or content delivery at scale
• Prior work in FDE-style or embedded delivery models where your team shipped inside a client codebase and was evaluated by their engineering standards, not just deliverable milestones
• Comfort with the ambiguity of 1P stack environments: you have debugged undocumented internal tools, extended proprietary frameworks, and figured out how to make external expertise land inside a closed ecosystem
• A personal reputation for architectural clarity: the person colleagues call when a problem needs to be drawn, not just describe
• Contributions to the ML/AI community: open source, publications, conference talks, or influential architectural patterns

Who Thrives Here

The Fractalite mindset is curious, rigorous, and impact driven. You will thrive in this role if you:

• Enjoy being client-facing and accountable for outcomes.
• Are comfortable navigating ambiguity, scale, and complex stakeholder environments.
• Believe great platforms come from strong engineering culture plus disciplined execution.
• See AI not as a novelty, but as a core enterprise capability that must be engineered responsibly.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Local to Bay area

1 day onsite @ Oakland office.

Role must interface with both business and engineers; expected to work directly with engineering teams.

Focus is on the enterprise data platform and data engineering; not an analytics/visualization role.

Core technical expectations

Strong data ecosystem background: experience leading data products or data warehousing initiatives.

Solid understanding of schemas, databases, and ETL (Extract, Transform, Load) processes; no hands-on coding expected but must be able to engage deeply with engineers and “know what they are talking about.”

Primary data warehouse platform: Snowflake.

Broader big data background acceptable if not purely Snowflake (e.g., Databricks, BigQuery, Redshift).

Current ETL tool: Informatica; hands-on Informatica expertise is not required.

Analytics/visualization not in scope; Power BI knowledge is a nice-to-have, not mandatory.

Role and scope

Titles vary across industry: product owner (PO), project manager, scrum master, TPM; at PG&E, similar roles may be labeled “product managers.”

Not seeking a pure scrum master or a typical external-facing PO who only writes requirements.

Role must interface with both business and engineers; expected to work directly with engineering teams.

Focus is on the enterprise data platform and data engineering; not an analytics/visualization role.

Core technical expectations

Strong data ecosystem background: experience leading data products or data warehousing initiatives.

Solid understanding of schemas, databases, and ETL (Extract, Transform, Load) processes; no hands-on coding expected but must be able to engage deeply with engineers and “know what they are talking about.”

Primary data warehouse platform: Snowflake.

Broader big data background acceptable if not purely Snowflake (e.g., Databricks, BigQuery, Redshift).

Current ETL tool: Informatica; hands-on Informatica expertise is not required.

Analytics/visualization not in scope; Power BI knowledge is a nice-to-have, not mandatory.

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Production Engineering at Pinterest is an evolution of our Site Reliability Engineering organization blending a hybrid of systems and software engineering with a focus on scaling, resiliency, reliability, performance, and efficiency. Our organization accomplishes this through building & integrating software, increasing automation, and infusing our knowledge & best practices into our Platform products so we can scale our large distributed systems to keep our customers happy, and our Pinners inspired. We also do this by developing short and long term embedded engagements with our engineering partners to help remove barriers, up-level reliability & best practices, and maintain a high consistent bar for reliability in a fast paced ever changing environment. We are always on a mission to improve reliability while also increasing engineering velocity, reducing toil and KTLO impact for both ourselves and our customers: fast, efficient, quality - we will accomplish all three!

What you'll do:

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• Lead our engineers to deliver on the biggest impact work across engineering to ensure we're infusing best practices into our products relating to reliability, scalability, performance and efficiency
  
• Drive technical architecture discussions; including being capable of driving and decision making for technology or applications that you have not had previous experience with
  
• Continuously assess your team's performance, address and coach under-performance, and recognize and promote high performance
  
• Create an inclusive and welcoming workplace where every team member feels valued and supported
  
• Foster an environment of open and honest communication, allowing team members to be safe to fail, encourage risk taking with a fail-fast mentality, and establish forums where they can share their ideas
  
• Empower engineers to develop their careers, matching their strengths with projects tailored to their skill levels, long-term skill development, personalities, and work styles
  
• Create an inspiring team charter and direction that align with the goals of the broader Production Engineering organization
  
• Develop strong partnerships with Product & Program Management partners across infrastructure by communicating a clear and impactful vision and priorities
  
• Establish team norms around planning, execution, and continuous improvement
  

What we're looking for:

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• 3+ years experience managing teams within an SRE, Production Engineering or other Platform/Infrastructure organizations
  
• Customer obsession: Demonstrated ability to work cohesively and build relationships with partners across engineering disciplines and capable of influencing without authority
  
• Familiarity with the concepts and use cases for SDLC including SCM tools, Build platforms, test frameworks, CI/CD products
  
• Familiar with usage and high level architecture of data platform technologies such as relational databases, storage & caching, key value stores, time series data stores, etc.
  
• Strong domain expertise in reliability concepts and best practices with the ability to innovate and provide thought leadership and direction in this problem space
  
• Hands on familiarity with public cloud platforms such as AWS, GCP, or Azure
  
• Knowledge of Linux systems internals and networking
  
• Thrive in an environment with a lot of ambiguity with the ability to be self sufficient and ruthlessly prioritize the highest impact projects
  
• Infrastructure technologies such as Docker, Kubernetes, Tensorflow, ElasticSearch, ZooKeeper, and Infrastructure as code (e.g. Terraform, Puppet, Chef, Ansible, Salt, Fabric, etc)
  
• Heavy bias toward action; able to drive resolution and making quick decisions balancing being data driven along with leveraging your experience & judgement
  

In-Office Requirement Statement:

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• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
  

Relocation Statement:

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• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-REMOTE

#LI-JT1

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

Open date: June 10, 2025

Most recent review date: Sunday, Feb 15, 2026 at 11:59pm (Pacific Time)

Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Monday, Feb 1, 2027 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

The Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley invites applications for a pool of qualified temporary instructors to teach Electrical Engineering or Computer Science courses should an opening arise. These are not tenure-track positions - selected candidates will hold the title of Lecturer. Screening of applicants is ongoing and will continue as needed. The number of positions varies from semester to semester, depending on the needs of the department. Due to budget restrictions, no funding is available for visa or relocation expenses.

In addition to lecturing responsibilities, general duties for these positions include holding office hours, assigning grades, advising students, preparing course materials (e.g. syllabus), and maintaining a course website.

The department seeks candidates who can support the success of all students through inclusive curriculum, classroom environment, and pedagogy in higher education through their teaching. UC Berkeley has an excellent benefits package as well as a number of policies and programs to support employees as they balance work and family, if applicable.

Please note: The use of a lecturer pool does not guarantee that an open position exists. See the review date specified in AP Recruit to learn whether the Department is currently reviewing applications for a specific position. If there is no future review date specified, your application may not be considered at this time.

Labor Contract:

Department:

Division:

School:

The minimum qualification required to be considered an applicant for the position is a Bachelor's degree (or equivalent international degree). Must be met by the time of application.

The following additional qualifications are required by the start date of the job. Advanced degree or four years teaching and/or industry experience.

Experience in teaching courses in Electrical Engineering or Computer Science, particularly courses with 200+ students. Experience managing large course staff.

Ability to support the success of all students through inclusive curriculum, classroom environment, and pedagogy.

• Cover Letter (Optional)

  
  

• Curriculum Vitae - Your current and updated C.V.

  
  

• Statement of Teaching - Please discuss prior teaching experience, qualifications (including teaching evaluations, if available), teaching approach, and future teaching interests. This can include, for example, specific efforts, accomplishments, and future plans to support the success of all students through inclusive curriculum, classroom environment, and pedagogy.

  
  
  

  The teaching statement must include information on the course(s) the applicant is qualified to teach (after reviewing our list of courses: academics/courses).

  
  
  

  Courses of particular interest in the Computer Science division include CS 10, CS 61A, CS 61B, CS 70, CS 88, CS C8, CS C100, CS 160, CS 169, CS 170, CS W186, CS 188, CS 189, CS 194-100*, CS 195, CS 370, and CS 375. *Note: Candidates qualified to teach CS 194-100 possess teaching experience and a background covering the intersection of social justice and technology.

  
  
  

  Courses of particular interest in the Electrical Engineering division include EE 16A , EE 16B, EE 192, and EE 247B.

  
  

• 3 required (contact information only)

References will only be contacted at the finalist stage. We will seek candidate permission before contacting references.

Help contact:

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

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• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  
• UC Sexual Violence and Sexual Harassment Policy
  
• UC Anti-Discrimination Policy
  
• APM - 035: Affirmative Action and Nondiscrimination in Employment