Engineering Structures Jobs Full Time Jobs in Emerald Hills, CA

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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 600 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, machine learning, statistics, or related field
  
• 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:
  
  
  • 
    
  • 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

#LI-SM4

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:

A fast-growing robotics company is building autonomous systems designed to automate repetitive tasks within the global infrastructure and construction sector. The company’s mission is to help address workforce shortages while accelerating the development of critical infrastructure projects.

Their robotics platforms combine advanced autonomous navigation, cloud software, and intelligent field tools to improve precision and efficiency across construction environments. With a growing fleet of robots already deployed across multiple project sites globally, the company is developing the next generation of automation tools used in areas such as infrastructure development, surveying, energy projects, and large-scale construction.

The company is seeking a Full-stack Developer to design and maintain the software systems that power its robotics ecosystem — including operator dashboards, cloud infrastructure, and applications that interface with robots operating in the field.

This role will contribute to building reliable tools for mission planning, fleet monitoring, and communication between cloud systems and robotic platforms. The position involves close collaboration with robotics engineers, field operations teams, and product stakeholders to ensure the software delivers measurable impact in real-world environments.

Key Responsibilities

• Design and develop full-stack applications for device management, mission control, and fleet coordination.
• Build and maintain mobile applications used by field operators.
• Develop desktop applications used to interface with robotic systems.
• Create web dashboards and APIs for mission planning, telemetry visualization, and operational data analysis.
• Integrate cloud infrastructure for data storage, monitoring, and deployment.
• Ensure reliable communication between cloud services and deployed robotic systems.
• Collaborate with robotics, product, and field teams to deliver integrated software functionality.
• Write technical documentation for APIs, system architecture, and software modules.
• Optimize systems for scalability, reliability, and performance in field environments.
• Requirements
• Education
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

Experience

• 4+ years of professional full-stack development experience.
• Strong experience with JavaScript / TypeScript using modern frameworks such as React, Next.js, and Node.js.
• Strong UI/UX development experience using modern CSS frameworks.
• Experience building mobile applications using React Native.
• Experience developing cross-platform desktop applications.
• Production experience with cloud platforms such as AWS including APIs, storage, and deployment pipelines.
• Strong understanding of software architecture, testing methodologies, and performance optimization.
• Proficiency with development tools including Git, issue tracking systems, and CI/CD pipelines.

Soft Skills

• Strong analytical and problem-solving ability.
• Ability to collaborate effectively in a fast-paced engineering environment.
• Strong ownership mindset and communication skills.
• Preferred Qualifications
• Experience working with robotics systems or robotics middleware.
• Familiarity with real-time communication protocols such as WebSockets or MQTT.
• Experience working with IoT devices, connected hardware, or industrial systems.
• Experience working with performance-sensitive or multi-threaded applications.
• Experience with containerization technologies such as Docker or Kubernetes.

Code Red is Partnered with a fast-growing startup. They are a software company in the healthtech space. Series D round of funding, located in San Francisco, New York City, + Seattle.

What you’ll do:

• Product Security Engineering and Software Security Engineering work, Bug Bounty, Vulnerability Management, and core ProdSec/AppSec management work.
• Will be taking over a small security team and growing it.
• Work with Product and Engineering teams to push out products.
• Collaborate with engineering, mitigate security risks, and support shipping quickly.
• Support threat modeling, shifting left, building tooling, and automating processes.
• Review code designs and pull requests, SSDLC, not a generalist/SecOps role.

Does this sound like you?

• 8+ years' exp. working on Application or Product Security Engineering teams.
• True Leadership experience, a small team is fine, but needs to have true management experience, able to influence and build a team + Engineering.
• Proven track record of starting and scaling a successful Product Security program.
• Excited about integrating security into product delivery without slowing things down.
• Passion for security and technology, bonus points for SWE background.

[leveling Engineering Manager or Sr. Engineering Manager, up to $350K base salary + equity]

*Direct-Hire/Permanent - must be located in San Francisco, New York City, or Seattle*

Cannot wait to hear more about this position?

Click apply below or reach out to Erin Barry ( ) today, and they will share more information and details about the role.

Code Red Partners are extremely committed to working with equal opportunity employers helping build a diverse and inclusive workforce within Cyber Security. We put the people we work with at the heart of everything we do and dedicate all we do to playing a part in developing an industry that represents a variety of backgrounds, perspectives, and skills.

VP of Engineering

AI-Driven Marketing Orchestration Platform

Overview

Our client is building an AI-native marketing orchestration platform designed to optimize creative generation, media spend, and performance through multi-agent systems. The platform will initially power a portfolio of marketing agencies and evolve into a standalone SaaS business. This is a foundational engineering leadership role.

Core Mandate

Build and ship a production-grade AI platform that:

• Reliably manages multi-agent workflows
• Handles enterprise-scale marketing spend
• Iterates rapidly based on real customer feedback
• Balances speed with system reliability

What Success Looks Like (First 12 Months)

• Working production system used by real customers
• Reliable multi-agent workflows (no catastrophic failure modes)
• High iteration velocity (weekly / bi-weekly shipping cadence)
• Strong early engineering team (5–8 people)
• Clear product traction and engagement

Key Responsibilities

Architecture & Systems

• Design and build multi-agent orchestration systems
• Ensure reliability in probabilistic workflows (failure handling, guardrails)
• Own backend architecture, data pipelines, and integrations (ad platforms, CRM, analytics)
• Implement observability, monitoring, and cost controls

Hands-On Development

• Write production code daily in early stages
• Review and improve code from team
• Guide AI-assisted development workflows (Cursor, Claude, etc.)
• Ensure code quality and security

Product & Iteration

• Work directly with customers to refine product
• Ship quickly and iterate based on feedback
• Balance MVP speed with enterprise reliability

Team Leadership

• Hire and lead a small elite engineering team
• Set engineering standards and velocity
• Mentor developers and enforce accountability

Required Experience

• Experience building ad tech or marketing technology systems
• Experience deploying AI / LLM systems to production
• Experience with multi-agent or orchestration workflows
• Strong backend / distributed systems experience
• Experience leading engineering teams (5–20 people)
• Must be hands-on and capable of coding

Preferred Background

• AI-native SaaS or adtech companies
• Experience at high-growth startups

Key Traits

• Builder mindset (not a pure manager)
• High technical rigor
• Mentally flexible (not dogmatic about tools)
• Customer-focused
• Moves fast but cares about quality

Location

• Preferred: New York or Los Angeles
• Open: SF or remote for exceptional candidates

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

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.

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.

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.

We're seeking an Engineering Manager to build and lead the next generation of Pinterest's big data storage platform. You'll grow and guide a team working with cutting-edge open source technologies-especially Apache Iceberg-operating at exabyte scale to power the data that helps Pinners discover and do what they love.

What you'll do:

• 
  
• Own the technical vision and long-term roadmap of Pinterest's exabyte data lake storage
  
• Collaborate with stakeholders and partner teams across the organization to architect data lake storage and metadata management technologies to unlock big data and ML/AI innovations
  
• Drive engagement and collaboration with open source communities, such as Iceberg, Spark, and Flink, to effectively address our scaling challenges
  
• Act as a stalwart of technical quality and excellence on the team, ensuring the solutions we deliver have a high level of polish and reliability
  

What we're looking for:

• 
  
• Bachelor's degree in a relevant field such as Computer Science, or equivalent experience
  
• 2+ years of management experience, or 3+ years tech lead experience in a 5+ person team
  
• 8+ years of relevant industry experience in leading the design of large scale & production distributed systems.
  
• Deep knowledge with building distributed systems.
  
• Strong cross-functional collaborator and communicator.
  
• Strong people development skills.
  
  

In-Office Requirement Statement:

• 
  
• 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:

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

#LI-HYBRID

#LI-AH2

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: