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Netflix

Machine Learning Software Engineer L4/L5, Algorithms

Posted 2 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
100K-720K Annually
Mid level
Remote
Hiring Remotely in USA
100K-720K Annually
Mid level
Design, develop, and scale software systems for machine learning algorithms powering personalization. Collaborate with researchers and product teams to implement production-ready, distributed solutions, enable offline experiments and A/B tests, and improve engineering practices and systems across teams.
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Netflix is one of the world’s leading entertainment services with 278 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

The Role

As Netflix continues to grow, so do the opportunities to enhance our personalization systems and algorithms. We're looking for a passionate and talented Software Engineer for Machine Learning to join our Algorithms team. In this role, you will apply your expertise in software engineering to design, develop, and scale solutions for the machine learning algorithms that power the Netflix experience. You will work closely with our machine learning researchers, product managers, and other engineers to come up with new systems, improve existing ones, and enable offline experiments and A/B tests. For more details about software engineering for personalization at Netflix, see these links: 

  • Consolidating ML models

  • InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models

  • Evidence Personalization

  • Page Simulation for Better Offline Metrics at Netflix

  • RecSysOps

As a software engineer in the team, you will contribute to the next generation of algorithms used to generate the Netflix experience by driving the vision, requirements, design, implementation, testing, and ownership of software components essential for our algorithmic innovation. You will collaborate with our applied researchers and data scientists to implement scalable, flexible, production-ready solutions for our algorithms. You will also guide the team towards better software engineering practices and systems by identifying areas for improvement and mentorship. You will collaborate with other engineers to create solutions that are used beyond our team. To excel in this role, you should have a robust software engineering background, a keen sense of software engineering principles and design, a proven experience with large-scale applications involving machine learning, a love of learning, possess strong communication skills, and the ability to work well in large cross-functional teams.

What we are looking for:

  • A degree in Computer Science or a related field 

  • 4+ years of full time software engineering experience with a bachelor’s degree; or 2+ years of experience with a graduate degree

  • Excellent software design and development skills in Python along with Scala, Java, C++, or C#

  • Solid understanding of various software engineering best practices and their appropriate application

  • Experience building web-scale parallel and distributed computing systems

  • Experience with large-scale data frameworks such as Spark or Flink

  • Excellent collaboration skills

  • Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems

Preferred, but not required:

  • Experience building or enhancing personalization systems, machine learning platforms, search engines, or similar large-scale machine learning applications.

  • Experience building machine learning models or LLMs

  • Experience scaling and optimizing the training and serving of machine learning models

  • Experience with machine learning libraries TensorFlow, PyTorch, JAX or Keras

  • Experience with cloud computing platforms like AWS

  • Background in math, statistics, or numerical computation

  • Significant contributions to open-source projects

Note: Level and compensation are determined based on your demonstrated experience, skills, and interview performance. We have several open positions within the personalization, search,  and recommendations space. The specific role will be determined based on the candidate's skills and fit, which will be evaluated after the initial round.

What do we offer:

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 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.

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

Netflix New York, New York, USA Office

245 W 17th St, New York, NY, United States, 10011

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