ML Engineer designing and building AI applications for customers in production environments. Collaborating with data scientists and engineers to operationalize ML models with a hybrid work environment.
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
Internship in AI and machine learning for process optimization at Dräger. Develop predictive models and optimize processes with a cross - disciplinary team.
Machine Learning Research Intern at Bell Labs collaborating with scientists on innovative machine learning research and thesis projects in AI and telecommunications.
Developing solutions for MLOps platform at Itaú, the largest bank in Latin America. Collaborating with software engineering practices to enhance user experience in machine learning.
Develop Machine Learning systems and applications as part of Estadão's digital transformation initiative. Focus on AI algorithms and data - driven solutions to enhance business performance.
Machine Learning Engineer working with multidisciplinary teams to deploy AI/ML systems in Defence. Engaging with clients, troubleshooting issues, and enhancing machine learning solutions.
Machine Learning Engineer at Lloyds Banking Group, supporting data - led innovation and AI solutions for financial services. Join a diverse team influencing the lives of 30m+ customers across the UK.
Intern in Machine Learning/Deep Learning at BeOne Medicines. Collaborating with leadership on high - impact AI modeling in Hematology and Oncology.
Machine Learning Engineer creating AI and ML solutions to transform operations in the Defense and Intelligence sectors. Focusing on optimizing data accessibility and operationalization of AI and ML systems.
Machine Learning Engineer creating AI solutions that enhance operations and accessibility in Defense and Intelligence sectors. Collaborating on technical innovations and deployments while leveraging cloud environments.