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Netflix

Software Engineer L4/L5 Training Platform, Machine Learning Platform

Reposted 8 Days Ago
Remote
Hiring Remotely in USA
100K-720K Annually
Mid level
Remote
Hiring Remotely in USA
100K-720K Annually
Mid level
In this role, you will design and build a platform for large-scale machine learning model training and optimize its operations. You'll create APIs for both ML practitioners and non-experts, focusing on enhancing cost-effectiveness and reliability in machine learning applications.
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At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. 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 the Training Platform team under our Machine Learning Platform (MLP) org. MLP’s charter is to maximize the business impact of all ML use cases at Netflix through highly reliable and flexible ML tooling and infrastructure that supports 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: 

  • Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company

  • Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training

  • Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform

Minimum Job Qualifications
  • Experience in ML engineering on production systems dealing with training or inference of deep learning models.

  • Proven track record of building and operating large-scale infrastructure for machine learning use cases

  • Experience with cloud computing providers, preferably AWS

  • Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects

  • Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes to ensure engineering excellence.

  • Excellent written and verbal communication skills

  • Comfortable working in a team with peers and partners distributed across (US) geographies & time zones.

Preferred Qualifications
  • Understand modern and real-world Machine Learning model development workflows and experience partnering closely with ML modeling engineers

  • Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.)

  • Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism

  • Expertise in the area of Generative AI, specifically when it comes to training foundation models, fine tuning them, and distilling them to smaller models

Generally, 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 $466,000.00 - $750,000.00. This compensation range will vary based on location.

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.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity 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.

Job is open for no less than 7 days and will be removed when the position is filled.

Top Skills

AWS
Bedrock
Databricks
Deep Learning
Generative Ai
Machine Learning
Openai
Sagemaker

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