Machine Learning Engineer developing and implementing ML models for lending at Blue Whale Lending LLC. Collaborating with teams to enhance data insights and validate model performance.
About the role
- Product Manager responsible for building foundational technology for Netflix Ads. Leading the development of composable machine learning infrastructure across product teams with a focus on user experience.
Responsibilities
- Define and own the end-to-end product vision for a shared ML architecture that spans every Netflix Ad Suite surface
- Deliver a platform (APIs, SDKs, UI) that our product teams can plug into without reinventing infrastructure
- Establish governance, privacy, and safety standards working closely with Legal, and Privacy to prevent “patchy ML” and ensure responsible outcomes
- Partner with Experience Design to invent next-gen workflows and agents that dramatically reduce task time and eliminate repetitive context switching
- Serve as the connective tissue across PMs in targeting, creatives, reporting, insights, and more; aligning roadmaps and eliminating duplicative work
- Integrate third-party applications and so that customers can interface with Netflix Ad Suite through systems they already know.
- Define and track success metrics such as workflow time reductions, platform adoption, and partner satisfaction, iterating quickly based on data and feedback
Requirements
- 10+ years of Product Management experience with a proven track record of launching and scaling foundational tech infrastructures
- Ability to deliver a comprehensive roadmap and vision for the future of machine learning supported workflows, catering to varied customer groups
- Deep understanding of the software and components that powers modern advertising, and machine learning
- Proven experience working with cross-functional teams, including operations teams, design, engineering, data foundations, privacy, legal, and external technology providers
- Familiarity with legal compliance and the evolving landscape of data privacy regulations worldwide
Benefits
- Health Plans
- Mental Health support
- 401(k) Retirement Plan with employer match
- Stock Option Program
- Disability Programs
- Health Savings and Flexible Spending Accounts
- Family-forming benefits
- Life and Serious Injury Benefits
- Paid leave of absence programs
- Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off
- Full-time salaried employees are immediately entitled to flexible time off
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Applied ML Engineer contributing to machine learning and perception tasks for edge - intelligent maritime systems. Collaborating with cross - functional teams to deliver real - world AI solutions.
AI/ML Engineer building data science and AI solutions for Pharma and MedTech clients on Azure. Collaborating with teams to deliver end - to - end machine learning projects.
ML Engineering Lead at Saris AI tackling multi - modal AI systems in banking. Drive technical direction and build high - performing teams in an early - stage startup environment.
Machine Learning Engineer designing and training lightweight ASR models for mobile devices at Plaud. Contributing to optimization, multilingual data management, and deployment collaboration.
Machine Learning Engineer designing post - processing test suites for AI interaction systems at Plaud Inc. Collaborating on speech algorithm training and user experience optimization in San Francisco.
Senior MLOps Engineer deploying ML - powered applications at Allica Bank. Building, prototyping, and ensuring the reliability of AI tools for SMEs.
Intermediate AI/ML Engineer designing and deploying machine learning solutions for video security. Join Solink to transform video security into real - time operational insights in a hybrid work environment.
Senior Machine Learning Engineer for Toyota Connected developing state - of - the - art solutions for in - vehicle Voice Assistants. Collaborating with teams and mentoring junior members to drive innovation in machine learning technology.
MLOps Engineer leading large - scale model deployments and managing CI/CD pipelines in GCP ecosystem. Focus on operational excellence and implementing observability frameworks for AI systems.