Codashop Ml Philippines Jobs in Usa
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About Us
We're continuing to build a transformative healthcare accreditation platform that is revolutionizing how our clients and new hospitals manage compliance, quality improvement, and regulatory processes. Our platform combines cutting-edge technology with deep healthcare domain expertise to solve real problems for healthcare organizations nationwide.
The Opportunity
The goal is to have interns turn into full time employees; Therefore, you will be given full time responsibilities day one. To add onto that, you will be working in a high velocity growth startup and will be required to move fast. You'll work directly with our engineering team on a production healthcare platform, gaining hands-on experience with enterprise-grade systems while making real contributions that impact our product and customers.
Compensation Structure: Base position is unpaid, however qualified candidates may receive upfront equity compensation based on their experience level and demonstrated capabilities. We evaluate each applicant individually and offer equity packages commensurate with their potential contribution.
What You'll Do
*During the internship you may choose the area to focus on...
Application Testing & Quality Assurance
- Design and execute comprehensive test plans for our healthcare portal
- Perform manual testing across web applications, APIs, and integrations
- Identify and document bugs, usability issues, and edge cases
- Test healthcare compliance features (HIPAA, document security, audit trails)
Test Automation Development
- Build automated test suites using modern testing frameworks
- Develop API testing scripts for healthcare data integrations
- Create performance testing scenarios for document upload/processing
- Implement continuous testing pipelines with CI/CD integration
AI/ML Quality Support
- Collaborate with our AI team on document processing accuracy testing
- Help validate machine learning models for healthcare document extraction
- Design test datasets for training and validation of AI systems
- Analyze and report on AI/ML model performance and data quality
Data Engineering Quality Assurance
- Develop data quality monitoring and validation processes
- Create automated checks for data integrity across MongoDB systems
- Build dashboards and alerts for data quality metrics
- Support ETL pipeline testing and validation
Process Improvement & Strategy
- Analyze current QA processes and identify optimization opportunities
- Research and recommend new testing tools and methodologies
- Participate in technical decision-making and sprint planning
- Document QA best practices and create team knowledge base
What We're Looking For
Required Qualifications:
- Currently pursuing or recently completed degree in Computer Science, Engineering, or related field
- Strong understanding of software testing principles and methodologies
- Experience with at least one programming language (Python, JavaScript, Java, etc.)
- Basic knowledge of databases (SQL/NoSQL) and API testing
- Excellent problem-solving skills and attention to detail
- Strong communication skills and ability to work in a collaborative environment
Preferred Qualifications:
- Experience with test automation frameworks (Selenium, Pytest, Jest, etc.)
- Knowledge of healthcare IT, compliance requirements, or regulated industries
- Familiarity with cloud platforms (AWS) and DevOps practices
- Experience with data analysis, ETL processes, or machine learning
- Previous internship or project experience in QA/testing roles
Technical Skills We'd Love to See:
- Testing Tools: Selenium, Postman, Jest, Pytest, Cypress
- Programming: Python, JavaScript, SQL
- Databases: MongoDB, SQL databases
- Cloud/DevOps: AWS, Docker, CI/CD pipelines
- Data Tools: Pandas, data validation frameworks
- Version Control: Git, GitHub
What You'll Gain
Professional Development:
- Real Impact: Your work directly affects a production healthcare platform used by hospitals
- Mentorship: Work closely with senior engineers and receive structured feedback
- Healthcare Domain Knowledge: Learn about healthcare compliance, accreditation, and regulatory requirements
- Enterprise Technology: Gain experience with production-grade systems, security, and scalability
Technical Skills:
- Advanced testing methodologies and automation frameworks
- Healthcare data processing and compliance requirements
- AI/ML model testing and validation techniques
- Data engineering and quality assurance practices
- Modern DevOps and CI/CD practices
Career Opportunities:
- Immediate Value: Potential upfront equity compensation based on qualifications
- Strong potential for full-time conversion based on performance
- Network with healthcare technology professionals
- Portfolio of real-world healthcare technology projects
- Experience that's highly valued in the growing healthtech sector
Our Tech Stack
- Frontend: React, Modern CSS
- Backend: Node.js, TypeScript, Python, RESTful APIs
- Database: MongoDB, with future SQL integrations
- Cloud: AWS (EC2, S3, Lambda, RDS)
- AI/ML: Document processing, natural language processing
- Security: HIPAA compliance, encryption, audit logging
- DevOps: Docker, GitHub Actions, automated testing
Compensation & Equity
- Base Position: Unpaid educational internship
- Equity/Stock Compensation: Available upfront based on applicant qualifications and experience level
Our Hiring Process
We believe in a transparent and thorough selection process that respects your time while ensuring mutual fit:
- Initial Screening Call We'll discuss your background, experience, and career goals, while providing an overview of the role and our team culture.
- Technical Interview We'll have an in-depth discussion about your experience and explore related technical concepts. You should be prepared to walk through every aspect of quality assurance as it pertains to your resume.
Ready to apply? We look forward to hearing from you!
MedLaunch is an equal opportunity employer committed to diversity and inclusion.
GENERAL SUMMARY:
The Manager of AI Enablement (Senior) leads the development and execution of Element Care’s internal approach to artificial intelligence. This role defines AI standards, policies, and best practices while enabling staff across the organization to adopt AI safely, ethically, and effectively. Reporting to the IT department, this position acts as a trusted advisor to leaders and end users, shaping AI governance, vendor strategy, training, and enterprise enablement.
ESSENTIAL RESPONSIBILITIES:
• Define and maintain organizational AI standards, policies, and governance frameworks.
• Lead the deployment of off-the-shelf AI solutions, including ambient documentation, predictive analytics, administrative automation, and clinical decision support tools.
• Enable responsible use of generative AI across administrative and operational functions.
• Conduct continuous workflow analysis to identify automation and AI-enablement opportunities.
• Evaluate AI and AI/ML models, tools, and vendor solutions for suitability, risk, and value.
• Partner with IT, data, analytics, and platform teams to align AI initiatives with enterprise architecture.
• Provide oversight and guidance on AI-enabled workflows, automation, and agent capabilities.
• Measure, monitor, and report on AI initiative outcomes, value realization, and performance.
• Build business cases and recommendations for future AI investments.
• Serve as the primary advisor to leaders and teams on AI use cases, risks, and governance.
• Monitor regulatory, ethical, and industry developments related to AI.
• Help establish and mature a scalable AI enablement and governance operating model.
• Influence adoption and consistency without direct authority.
• Perform other duties as assigned.
JOB SPECIFICATION:
• 6–10+ years of relevant professional experience, including applied AI, automation, analytics, or emerging technology leadership.
• Demonstrated experience evaluating AI/ML models, vendor solutions, or AI platforms.
• Experience with vendor management, solution selection, or hands-on implementation required.
• Demonstrated experience defining standards, policies, or enterprise enablement programs.
• Healthcare or other regulated industry experience strongly preferred.
• Strong understanding of applied AI, AI/ML evaluation, governance, risk, and ethical considerations.
• Ability to translate complex concepts into practical organizational guidance.
• Experience developing business cases and value narratives for technology investments.
• Executive-level communication and facilitation skills.
• Proven ability to operate independently and influence across the enterprise.
• Strategic mindset with a pragmatic, implementation-oriented approach.
Compensation details: 13 Yearly Salary
PI71b2d5685c13-3631
Get Hired by taking action.
If you just graduated (or you're about to) and the job search is already feeling confusing, you're not imagining it.
A degree proves you can learn—but employers hire for job readiness: projects that look like real work, current tech stacks, interview confidence, and the ability to contribute on day one.
That's why many new grads send hundreds of applications and still hear nothing back.
It's not because you're "not smart enough.” It's because most entry-level pipelines are crowded, and hiring teams filter heavily for candidates who look production-ready.
We are actively considering candidates for entry-level software engineering and data roles, especially Java full stack, Java/Python development, DevOps automation, data analytics, data engineering, data science, and ML/AI—full-time opportunities aligned to client needs.
Our core emphasis remains Java/Full Stack/DevOps and Data/Analytics/Engineering/ML.
SynergisticIT focuses on two high-demand lanes: Java / Full Stack / DevOps and Data (Data Analyst, Data Engineer, Data Scientist) + ML/AI—so you don't graduate with scattered skills, you graduate with an employable stack.
SynergisticIT since 2010, has helped candidates land full-time roles at major organizations (examples often cited include Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Banking, Wayfair, Client, Client, and more) with offers commonly in the $95k–$154k range depending on role and skill depth.
For a new grad, the bigger message isn't the number—it's that results require a structured pathway, not random applications.
Here's a realistic way to think about your advantage as a fresh graduate: you're early enough to build the right foundation before bad habits set in.
If you master fundamentals—coding, debugging, data structures, system thinking—and then layer modern tools on top (frameworks, cloud, CI/CD, analytics stacks), you become the kind of "entry-level” candidate who actually feels like a safe hire.
What roles are companies hiring for right now? A typical market demand pattern is clear: organizations still need entry-level software programmers, Java full stack developers, Python/Java developers, DevOps-focused engineers, and on the data side data analysts, BI analysts, data engineers, data scientists, and machine learning engineers.
The strongest candidates aren't "tool collectors”—they're people who can show end-to-end capability: build an API, connect a database, deploy a service, analyze data, explain results, and handle interviews calmly.
Why fresh grads get stuck— Fresh grads often struggle for four predictable reasons: Resume doesn't match job keywords (ATS filters you out).
Projects look like school assignments (not production-aligned).
Interview skills are undertrained (DSA, system design, SQL, behavioral).
No structured pipeline (random applying without feedback loops).
A job-placement-first approach addresses these systematically: build the right portfolio, practice the right interview questions, align your tech stack to roles, and keep improving until the market says "yes.” Who this path fits best If you're a recent graduate, you'll likely fit if you match any of these: New grads in CS, Engineering, Math, or Statistics with limited job experience Students finishing Bachelor's or Master's programs who need a real hiring plan Candidates who apply consistently but don't get callbacks Candidates who reach interviews but struggle to close International students on F-1/OPT who need a job plan for STEM extension/H-1B timing Graduates with strong academics but thin practical experience SynergisticIT helps STEM extension and work authorization pathways, and for candidates who need long-term stability, support related to H-1B and green card processes as part of employer-side realities.
If you're tired of guessing, stop treating your job search like a lottery.
Treat it like a project with milestones: skills → portfolio → interview readiness → targeted applications → scheduled interviews → offer.
If you want to explore the program directly, here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Contact & get a roadmap: Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? How OPT Students Can Land Tech Jobs – SynergisticIT Bottom line for fresh grads: Your degree is the starting line, not the finish line.
If you want to get hired faster, you don't need "more random courses.” You need a guided, job-focused path and the right people around you.
In tech, it's not just what you learn—it's how you learn and who you build with that decides how far you go.
Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.
Able to operate independently in low structure environments, collaborate across business and IT, and deliver high quality, AI ready data ecosystems.
Role Purpose Establish, advance, and mature data quality and governance capabilities in a green field, low maturity data environment.
Support enterprise analytics, BI, and AI/ML readiness through SQL/ETL engineering, data profiling, validation, stewardship, metadata management, and early stage data architecture.
Drive long term improvement of data standards, definitions, lineage, and quality processes.
Key Responsibilities Data Quality & Engineering Perform data audits, profiling, validation, anomaly detection, and quality gap identification.
Develop automated data quality rules and validation logic using T SQL, SQL Server, stored procedures, and indexing strategies.
Build and maintain SSIS packages for validation, cleansing, transformation, and error detection workflows.
Troubleshoot ETL/ELT pipelines, data migrations, integration failures, and data load issues.
Conduct root cause analysis and implement preventive and long term remediation solutions.
Optimize SQL queries, tune stored procedures, and improve data processing performance.
Document audit findings, validation processes, data flows, standards, and quality reports.
Build dashboards and reports for data quality KPIs using Power BI/Tableau.
Data Stewardship & Governance Define, maintain, and enforce data quality standards, business rules, data definitions, and governance policies.
Monitor datasets for completeness, accuracy, timeliness, consistency, and compliance.
Ensure proper and consistent data usage across departments and systems.
Maintain business glossaries, data dictionaries, metadata repositories, and lineage documentation.
Partner with IT, data engineering, and business teams to support governance initiatives and compliance requirements.
Provide training on data entry, data handling, stewardship practices, and data literacy.
Collaborate with cross functional teams to identify recurring data issues and recommend preventive solutions.
GreenField / LowMaturity Environment Architect initial data quality frameworks, validation layers, governance artifacts, and ingestion patterns.
Establish scalable data preparation workflows supporting analytics, BI, and AI/ML readiness.
Mature data quality and governance processes from ad hoc to standardized, automated, and measurable.
Drive adoption of data quality and governance practices across business and technical teams.
Support long term evolution of enterprise data strategy and governance maturity.
Required Technical Skills Advanced T SQL, SQL Server development, debugging, and performance tuning.
SSIS development, deployment, and troubleshooting.
Data profiling, validation rule design, quality scoring, and measurement techniques.
ETL/ELT pipeline design, debugging, and optimization.
Data modeling (conceptual, logical, physical).
Metadata management and lineage documentation.
Reporting and dashboarding with Power BI, Tableau, or similar tools.
Strong documentation and communication skills.
Preferred Skills Knowledge of DAMA DMBoK, DCAM, MDM concepts, and governance frameworks.
Experience in low maturity/green field data environments.
Familiarity with AI/ML data readiness and feature store aligned data structuring.
Cloud data engineering exposure (Azure, Databricks, GCP).
Education Bachelor’s degree in Information Systems, Computer Science, Data Science, Statistics, Business Analytics, or related field.
Master’s degree preferred.
Certifications (Preferred) DAMA CDMP (Associate/Practitioner) EDM Council DCAM ASQ Data Quality Credential Collibra Data Steward Certification Certified Data Steward (eLearningCurve) Cloud/AI certifications (Azure, Databricks, Google)
Get Hired by taking action.
If you just graduated (or you're about to) and the job search is already feeling confusing, you're not imagining it.
A degree proves you can learn—but employers hire for job readiness: projects that look like real work, current tech stacks, interview confidence, and the ability to contribute on day one.
That's why many new grads send hundreds of applications and still hear nothing back.
It's not because you're "not smart enough.” It's because most entry-level pipelines are crowded, and hiring teams filter heavily for candidates who look production-ready.
We are actively considering candidates for entry-level software engineering and data roles, especially Java full stack, Java/Python development, DevOps automation, data analytics, data engineering, data science, and ML/AI—full-time opportunities aligned to client needs.
Our core emphasis remains Java/Full Stack/DevOps and Data/Analytics/Engineering/ML.
SynergisticIT focuses on two high-demand lanes: Java / Full Stack / DevOps and Data (Data Analyst, Data Engineer, Data Scientist) + ML/AI—so you don't graduate with scattered skills, you graduate with an employable stack.
SynergisticIT since 2010, has helped candidates land full-time roles at major organizations (examples often cited include Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Banking, Wayfair, Client, Client, and more) with offers commonly in the $95k–$154k range depending on role and skill depth.
For a new grad, the bigger message isn't the number—it's that results require a structured pathway, not random applications.
Here's a realistic way to think about your advantage as a fresh graduate: you're early enough to build the right foundation before bad habits set in.
If you master fundamentals—coding, debugging, data structures, system thinking—and then layer modern tools on top (frameworks, cloud, CI/CD, analytics stacks), you become the kind of "entry-level” candidate who actually feels like a safe hire.
What roles are companies hiring for right now? A typical market demand pattern is clear: organizations still need entry-level software programmers, Java full stack developers, Python/Java developers, DevOps-focused engineers, and on the data side data analysts, BI analysts, data engineers, data scientists, and machine learning engineers.
The strongest candidates aren't "tool collectors”—they're people who can show end-to-end capability: build an API, connect a database, deploy a service, analyze data, explain results, and handle interviews calmly.
Why fresh grads get stuck— Fresh grads often struggle for four predictable reasons: Resume doesn't match job keywords (ATS filters you out).
Projects look like school assignments (not production-aligned).
Interview skills are undertrained (DSA, system design, SQL, behavioral).
No structured pipeline (random applying without feedback loops).
A job-placement-first approach addresses these systematically: build the right portfolio, practice the right interview questions, align your tech stack to roles, and keep improving until the market says "yes.” Who this path fits best If you're a recent graduate, you'll likely fit if you match any of these: New grads in CS, Engineering, Math, or Statistics with limited job experience Students finishing Bachelor's or Master's programs who need a real hiring plan Candidates who apply consistently but don't get callbacks Candidates who reach interviews but struggle to close International students on F-1/OPT who need a job plan for STEM extension/H-1B timing Graduates with strong academics but thin practical experience SynergisticIT helps STEM extension and work authorization pathways, and for candidates who need long-term stability, support related to H-1B and green card processes as part of employer-side realities.
If you're tired of guessing, stop treating your job search like a lottery.
Treat it like a project with milestones: skills → portfolio → interview readiness → targeted applications → scheduled interviews → offer.
If you want to explore, here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Contact & get a roadmap: Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? How OPT Students Can Land Tech Jobs – SynergisticIT Bottom line for fresh grads: Your degree is the starting line, not the finish line.
If you want to get hired faster, you don't need "more random courses.” You need a guided, job-focused path and the right people around you.
In tech, it's not just what you learn—it's how you learn and who you build with that decides how far you go.
Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.
Resume submissions may be shared with our JOPP team database also.
Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume
Get Hired by taking action.
If you just graduated (or you're about to) and the job search is already feeling confusing, you're not imagining it.
A degree proves you can learn—but employers hire for job readiness: projects that look like real work, current tech stacks, interview confidence, and the ability to contribute on day one.
That's why many new grads send hundreds of applications and still hear nothing back.
It's not because you're "not smart enough.” It's because most entry-level pipelines are crowded, and hiring teams filter heavily for candidates who look production-ready.
We are actively considering candidates for entry-level software engineering and data roles, especially Java full stack, Java/Python development, DevOps automation, data analytics, data engineering, data science, and ML/AI—full-time opportunities aligned to client needs.
Our core emphasis remains Java/Full Stack/DevOps and Data/Analytics/Engineering/ML.
SynergisticIT focuses on two high-demand lanes: Java / Full Stack / DevOps and Data (Data Analyst, Data Engineer, Data Scientist) + ML/AI—so you don't graduate with scattered skills, you graduate with an employable stack.
SynergisticIT since 2010, has helped candidates land full-time roles at major organizations (examples often cited include Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Banking, Wayfair, Client, Client, and more) with offers commonly in the $95k–$154k range depending on role and skill depth.
For a new grad, the bigger message isn't the number—it's that results require a structured pathway, not random applications.
Here's a realistic way to think about your advantage as a fresh graduate: you're early enough to build the right foundation before bad habits set in.
If you master fundamentals—coding, debugging, data structures, system thinking—and then layer modern tools on top (frameworks, cloud, CI/CD, analytics stacks), you become the kind of "entry-level” candidate who actually feels like a safe hire.
What roles are companies hiring for right now? A typical market demand pattern is clear: organizations still need entry-level software programmers, Java full stack developers, Python/Java developers, DevOps-focused engineers, and on the data side data analysts, BI analysts, data engineers, data scientists, and machine learning engineers.
The strongest candidates aren't "tool collectors”—they're people who can show end-to-end capability: build an API, connect a database, deploy a service, analyze data, explain results, and handle interviews calmly.
Why fresh grads get stuck— Fresh grads often struggle for four predictable reasons: Resume doesn't match job keywords (ATS filters you out).
Projects look like school assignments (not production-aligned).
Interview skills are undertrained (DSA, system design, SQL, behavioral).
No structured pipeline (random applying without feedback loops).
A job-placement-first approach addresses these systematically: build the right portfolio, practice the right interview questions, align your tech stack to roles, and keep improving until the market says "yes.” Who this path fits best If you're a recent graduate, you'll likely fit if you match any of these: New grads in CS, Engineering, Math, or Statistics with limited job experience Students finishing Bachelor's or Master's programs who need a real hiring plan Candidates who apply consistently but don't get callbacks Candidates who reach interviews but struggle to close International students on F-1/OPT who need a job plan for STEM extension/H-1B timing Graduates with strong academics but thin practical experience SynergisticIT helps STEM extension and work authorization pathways, and for candidates who need long-term stability, support related to H-1B and green card processes as part of employer-side realities.
If you're tired of guessing, stop treating your job search like a lottery.
Treat it like a project with milestones: skills → portfolio → interview readiness → targeted applications → scheduled interviews → offer.
If you want to explore, here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Contact & get a roadmap: Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? How OPT Students Can Land Tech Jobs – SynergisticIT Bottom line for fresh grads: Your degree is the starting line, not the finish line.
If you want to get hired faster, you don't need "more random courses.” You need a guided, job-focused path and the right people around you.
In tech, it's not just what you learn—it's how you learn and who you build with that decides how far you go.
Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.
Resume submissions may be shared with our JOPP team database also.
Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume
Qualifications: MLT - At least two years of college education and graduation from an approved MLT program or equivalent. Certification or equivalent is preferred if hired prior to 3/1/2024; required within 12 months for those hired/transferred into this position on or after 3/1/2024. No prior experience required for graduate of approved MLT program (certification eligible). Some knowledge of laboratory testing procedures. Some skill in performing various laboratory procedures and collecting specimens. Good customer service skills.
MLS - Bachelor's degree from an accredited college or university. MT/MLS/CLS certification or equivalent is preferred if hired prior to 3/1/2024; required within 12 months for those hired/transferred into this position on or after 3/1/2024. No prior work experience required for graduate of approved MT/MLS/CLS program (certification eligible). Thorough knowledge of laboratory testing procedures and equipment. Considerable skill in performing various laboratory tests and troubleshooting methodology and quality issues. Effective communication skills and ability to lead a laboratory workgroup.
EOE AA M/F/Vet/Disability
Sr. Data Engineer (Hybrid)
Chicago, IL
The American Medical Association (AMA) is the nation's largest professional Association of physicians and a non-profit organization. We are a unifying voice and powerful ally for America's physicians, the patients they care for, and the promise of a healthier nation. To be part of the AMA is to be part of our Mission to promote the art and science of medicine and the betterment of public health.
At AMA, our mission to improve the health of the nation starts with our people. We foster an inclusive, people-first culture where every employee is empowered to perform at their best. Together, we advance meaningful change in health care and the communities we serve.
We encourage and support professional development for our employees, and we are dedicated to social responsibility. We invite you to learn more about us and we look forward to getting to know you.
We have an opportunity at our corporate offices in Chicago for a Sr. Data Engineer (Hybrid) on our Information Technology team. This is a hybrid position reporting into our Chicago, IL office, requiring 3 days a week in the office.
As a Sr. Data Engineer, you will play a key role in implementing
and maintaining AMA's enterprise data platform to support analytics,
interoperability, and responsible AI adoption. This role partners closely with
platform engineering, data governance, data science, IT security, and business
stakeholders to deliver highquality, reliable, and secure data products. This
role contributes to AMA's modern lakehouse architecture, optimizing data
operations, and embedding governance and quality standards into engineering
workflows. This role serves as a
senior technical contributor within the team-providing mentorship to junior
engineers and implementing engineering best practices within the data platform function,
in alignment with architectural direction set by leadership.
RESPONSIBILITIES:
Data Engineering & AI Enablement
- Build and maintain scalable data pipelines and
ETL/ELT workflows supporting analytics, operational reporting, and AI/ML use
cases. - Implement best practice patterns for ingestion,
transformation, modeling, and orchestration within a modern lakehouse
environment (e.g., Databricks, Delta Lake, Azure Data Lake). - Develop highperformance
data models and curated datasets with strong attention to quality, usability,
and interoperability; create reusable engineering components and automation. - Collaborate with the Architecture Team, the Data
Platform Lead, and federated IT teams to optimize storage, compute, and
architectural patterns for performance and costefficiency. - Build model-ready data sets and feature
pipelines to support AI/ ML use cases; serve as a technical coordination point
supporting business units' AI-related infrastructure needs. - Collaborate with data scientists and AI Working
Group to operationalize models responsibly and maintain ongoing monitoring
signals.
Governance, Quality & Compliance
- Embed data governance, metadata standards,
lineage tracking, and quality controls directly into engineering workflows;
ensure technical implementation and alignment within engineering workflows. - Work with the Data Governance Lead and business
stakeholders to operationalize stewardship, classification, validation,
retention, and access standards. - Implement privacybydesign and securitybydesign
principles, ensuring compliance with internal policies and regulatory
obligations. - Maintain documentation for pipelines, datasets,
and transformations to support transparency and audit requirements.
Platform Reliability, Observability & Optimization
- Monitor and troubleshoot pipeline failures,
performance bottlenecks, data anomalies, and platformlevel issues. - Implement observability tooling, alerts,
logging, and dashboards to ensure endtoend reliability. - Support cost governance by optimizing compute
resources, refining job schedules, and advising on efficient architecture. - Collaborate with the Data Platform Lead on
scaling, configuration management, CI/CD pipelines, and environment management. - Collaborate with business units to understand
data needs, translate them into engineering requirements, and deliver
fit-for-purpose data solutions; share and apply best practices and emerging
technologies within assigned initiatives. - Work with IT Security and Legal/ Compliance to
ensure platform and datasets meet risk and regulatory standards.
Staff Management
- Lead, mentor, and provide management oversight
for staff. - Responsible for setting objectives, evaluating
employee performance, and fostering a collaborative team environment. - Responsible for developing staff knowledge and
skills to support career development.
May include other responsibilities as assigned
REQUIREMENTS:
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field preferred or equivalent work experience and HS diploma/equivalent education required.
- 5+ years of experience in data engineering within cloud environments
- Experience in people management preferred.
- Demonstrated hands-on experience with modern data platforms (Databricks preferred).
- Proficiency in Python, SQL, and data
transformation frameworks. - Experience designing and operationalizing
ETL/ELT pipelines, orchestration workflows (Airflow, Databricks Workflows), and
CI/CD processes. - Solid understanding of data modeling,
structured/unstructured data patterns, and schema design. - Experience implementing governance and quality
controls: metadata, lineage, validation, stewardship workflows. - Working knowledge of cloud architecture, IAM,
networking, and security best practices. - Demonstrated ability to collaborate across
technical and business teams. - Exposure to AI/ML engineering concepts, feature
stores, model monitoring, or MLOps patterns. - Experience with infrastructureascode
(Terraform, CloudFormation) or DevOps tooling.
The American Medical Association is located at 330 N. Wabash Avenue, Chicago, IL 60611 and is convenient to all public transportation in Chicago.
This role is an exempt position, and the salary range for this position is $115,523.42-$150,972.44. This is the lowest to highest salary we believe we would pay for this role at the time of this posting. An employee's pay within the salary range will be determined by a variety of factors including but not limited to business consideration and geographical location, as well as candidate qualifications, such as skills, education, and experience. Employees are also eligible to participate in an incentive plan. To learn more about the American Medical Association's benefits offerings, please click here.
We are an equal opportunity employer, committed to diversity in our workforce. All qualified applicants will receive consideration for employment. As an EOE/AA employer, the American Medical Association will not discriminate in its employment practices due to an applicant's race, color, religion, sex, age, national origin, sexual orientation, gender identity and veteran or disability status.
THE AMA IS COMMITTED TO IMPROVING THE HEALTH OF THE NATION
Apply NowShare Save JobRemote working/work at home options are available for this role.
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.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Machine Learning Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem - auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios - and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.
What you'll do:
- Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
- Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
- Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
- Use LLMs and generative AI to accelerate internal ML workflows - synthetic data generation, code generation, automated analysis, and rapid prototyping
- Use simulation to de-risk ML model deployments - validate new bidding and optimization strategies before they touch live traffic
- Define the technical direction for simulation and AI infrastructure and mentor engineers on the team
What we're looking for:
- Strong production Python skills and experience building simulation or modeling systems
- Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
- Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows - and good judgment about when they help vs. when they don't
- Adtech experience: you understand auction theory, RTB mechanics, and the dynamics of programmatic advertising
- Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
- Clear written communication: you'll be defining new technical directions and need to bring others along
- Ownership: you scope, design, and ship systems end-to-end with minimal direction
- Nice-to-Haves:
- Causal inference - uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
- Experience with discrete event simulation, Monte Carlo methods, or digital twins
- Reinforcement learning - using simulated environments for policy learning and evaluation
- Experience building agentic AI systems or multi-agent simulations
- Big data experience with Scala and Spark
- Systems programming experience in Zig or similar (C, C++, Rust)
- MLOps experience - model deployment, monitoring, and pipeline orchestration on AWS
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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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.
US based applicants only$123,696—$254,667 USDOur Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please completethis formfor support.
Duration: 11 Months (Contract to hire)
Location: Columbia, SC
Onsite Requirements: Partially onsite 3 days per week (Tue, Wed, Thurs) and as needed.
Standard work hours: 8:00 AM - 5:00 PM
**Credit check will be required**
Job Summary:
Day to Day:
- A typical day will involve a mix of hands-on coding, architectural design, and research.
- The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
- This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
- They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
Team: The team is an innovative, collaborative, and empowering environment. We are building the next generation of AI solutions for the enterprise in a fast-paced, project-oriented setting. This is a multi-platformed environment that values creativity, continuous learning, and a customer-focused mindset. The new engineer will play a crucial role in shaping our AI strategy and building foundational tools and accelerators that will drive innovation across the company.
Job Requirements:
**This is a new role to establish a core competency in agentic AI systems. This engineer will be pivotal in designing and deploying advanced AI agents and will build the foundational frameworks for future AI use cases across the organization.**
Required Experience:
Required Software and Tools (Hands on experience required):
- Python
- JavaScript/TypeScript
- AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
- AI Models (e.g. Claude, OpenAI, etc.)
- AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
- Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
- Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
- API Design
Python & AI/ML Libraries:
- Deep hands-on experience in Python for AI/ML development.
- Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
- Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
- Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
Minimum Required Education: Bachelor's degree-in Computer Science, Information Technology or other job related degree or 4 years relevant experience or Associates degree + 2 years relevant experience
Minimum Required Work Experience: 6years-of application development, systems testing or other job related experience.
Required Technologies: 3-6 years of hands-on experience in Artificial Intelligence, Machine Learning, or related fields.
Nice to have/Preferred skills:
- Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
- Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
- Experience developing autonomous agents using cloud-based AI services.
- Experience with prompt engineering techniques and model fine-tuning.
- Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
- Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
