ML Engineer L5, LLM Application Frameworks, Machine Learning Platform

Netflix is the world's leading streaming entertainment service with 260+ million paid memberships in over 190 countries enjoying TV series, documentaries, and feature films across a wide variety of genres and languages. Machine Learning drives innovation across all product functions and decision-support needs. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.

The Opportunity

We are looking for a driven Software Engineer to join a new team focussed on Foundation Model infra under our Machine Learning Platform (MLP) org. MLP's charter is to maximize the business impact of all ML at Netflix. We develop innovative ML infrastructure to support key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others.

In this role you will get to:

• Define the LLM and Foundation Model Application frameworks with agentic approaches for large-scale language applications
• Design and implement tooling around the productization of generative foundation models such as RAG, version control, and prompt management.
• Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts.

Minimum Job Qualifications

• 2-5 years of experience in ML engineering on production systems dealing with training or inference of deep learning models.
• Experience with LLM Ops tooling, LLM Agent APIs, and LLM orchestration frameworks and libraries like LangChain
• BS/MS in Computer Science, or a related field
• Experience with cloud computing providers such as AWS
• Comfortable with ambiguity, ability to take on and execute 0-1 projects
• Experience partnering closely with ML researchers
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience with training, fine-tuning, or serving large deep learning models, or LLMs, at the scale of millions of users.
• Experience with popular optimized LLM serving libraries such as DeepSpeed, TensorRT, or vLLM.
• Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism.
• Experience with cloud computing providers such as AWS

Recent Artifacts from the team

• Invited Paper at RecSys 2023 - InTune: RL based pipeline optimization for Deep RecSys
• Synergistic Signals: Exploiting Co-Engagement and Semantic Links via Graph Neural Networks
• Talk on heterogeneous compute environments for ML at Ray Summit 2023
• OSS LLM Serving & Benchmarking - Talk at ML Platform Meetup Dec 2023
• Opportunities for OSS LLMs in the Enterprise - Panel Discussion at ML Platform Meetup Dec 2023

Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top-of-market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $100,000 - $720,000.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer 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. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.