Research Engineer, Machine Learning L6

Job Description

The Role

Fast-paced innovation in the theory and practice of large language models (LLMs) is greatly helping to advance state-of-the-art in Search and Recommendation experiences. Hence we are looking for exceptional applied machine learning engineers to help us develop the technology to power future member experiences using the latest advances related to LLMs.

This role focuses on aligning and evaluating our member-facing algorithms to deliver high quality recommendations that maximize member satisfaction. In this role, you will aid applied research and product development by conceptualizing, designing, and implementing engineering improvements. To be successful in this role, you need solid software development skills, a love of learning, a passion for solving problems, a bias to action, and effective collaboration with cross-functional partners. Experience with quality and evaluation metrics for complex ML products, RLHF, human-in-the-loop data pipelines and reward modeling is preferred. You should excel at writing high-quality code, developing tools for model alignment and evaluation, and continuously enhancing quality metrics based on member feedback signals.

You may be a good fit if you have:
• Software engineering experience with a track record of delivering quality results.
• Proven experience with large scale recommender systems and the application of rewards to steer model outcomes
• Experience in developing standardized evaluation frameworks for context-dependent systems
• Proven expertise in training, fine tuning, aligning and evaluating LLMs and other large foundation models.
• Proven experience with RLHF, reward models, model quality and evaluation
• Strong problem-solving and debugging skills with complex ML systems
• Strong software development experience in languages such as Python and Java.
• Experience with Spark, TensorFlow, Keras, and PyTorch.
• Experience with GPUs and distributed systems
• Great interpersonal skills.
• Strong communication skills - written and verbal.
• Graduate degree in Computer Science, Statistics, or a related field.

Strong candidates may also have one or more of these additional areas of experience:
• Experience as a technical leader.
• Experience working with cross-functional teams.
• Experience in Search, Recommendations, Natural Language Processing, Conversational Agents, and Personalization.
• Experience building tools and capabilities to test and evaluate model robustness
• Experience with cloud computing platforms and large web-scale distributed systems.
• Experience in applied research in industrial settings.
• Open source contributions.
• Research publications at peer-reviewed journals and conferences on relevant topics.

Netflix's culture is an integral part of what makes us successful, and we approach diversity and inclusion seriously and thoughtfully. We are an equal-opportunity employer and celebrate diversity, recognizing that bringing together different perspectives and backgrounds helps build stronger teams. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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 - $990,000.

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 detail 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.

Jobcode: Reference SBJ-rjk5pw-18-119-118-169-42 in your application.