Machine Learning Engineer 4 - Product



Software Engineering, Product
Los Gatos, CA, USA
Posted on Wednesday, January 10, 2024
At Netflix our goal is to entertain the world. Our 200+ million members stream award-winning content, and play thousands of hours of games, from 190 countries. Everything that we build to delight our members, and all of the work we do to figure out how to do that better, relies on our extensive infrastructure, particularly the resources we rent from AWS. We invest heavily in this infrastructure as we are one of AWS’s biggest customers. We are always looking for ways to use these resources better. Algorithms and ML help us do this by being smarter about how we distribute the work across our fleet.
As a Machine Learning Engineer, you will join a team of Infrastructure Machine Learning Engineers who you will work closely with to develop new ways ML can improve the performance, efficiency and reliability of Netflix’s foundational systems. You will also help support existing systems that are designed to operate at Netflix scale and work with our infrastructure engineering teams to ensure the reliability of these systems.

In this role, you will:

  • Partner closely with Infrastructure Machine Learning Engineers to build systems designed to improve our extensive infrastructure.
  • Help Infrastructure Machine Learning Engineers maintain and support existing systems.
  • Use your experience supporting existing systems to inform how we can improve support processes to allow us to scale effectively.
  • Help evangelize this work with the broader Algos and ML community at Netflix.

You are:

  • Motivated by your curiosity for understanding how complex systems work, especially large scale cloud infrastructure and distributed systems.
  • Self-motivated to learn, with an ability to work closely with engineering and ML engineering partners.
  • A strong coder with experience in Python and standard ML frameworks like PyTorch and TensorFlow. Experience with languages like Java or C++ is a plus.
  • Some experience in implementing and productionizing models in large scale industrial settings is a plus.
  • Familiarity with optimization models with standard frameworks/solvers (e.g., XPress, cvxpy, Gurobi).
  • Familiarity with operational tooling for ML services (monitoring, alerting, etc.), and services for model hosting/serving.
  • Someone who has “strong opinions, loosely held”. You use data to back up your ideas and are willing to change your mind if new data comes to light.
  • Able to communicate your ideas clearly and succinctly with the right amount of detail to audiences with varying technical backgrounds.
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 $170,000 - $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 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.