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Software Engineer, ML Infra

Twitch

San Francisco, CA Remote permanent

Posted: January 22, 2026

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Quick Summary

Software Engineer, ML Infra, San Francisco, CA, with a strong background in machine learning and software development, and experience with cloud infrastructure and scalability.

Job Description

About Us

Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.

About the Role

Twitch connects millions of creators with millions of viewers. Our Machine Learning based recommendation and search systems power discovery products across Twitch and help users find content hyper-personalized for them. Twitch is looking for a Software Engineer to join our Machine Learning Infrastructure team. You will work with software engineers, applied scientists and product managers in our Models and Infrastructure group to build next-generation Machine Learning systems. The engineering team is responsible for enabling reliable and efficient productionization of Twitch personalization models, including owning the software and data systems to develop, train and manage our real time and batch models at scale. We own the ML platform and care about designing scalable and easy-to-use ML development environments and systems for our consumers. Experimentation is our bread-and-butter and you will have hands-on experience building and launching model-based experiments to improve products.

This role is based in San Francisco, CA.

You Will:

• Produce clean, high-quality, and well tested code

• Design and build scalable infrastructure to train, deploy and manage ML models

• Develop and automate software for ML workflows

• Optimize cost and performance of training and inference workloads

• Collaborate with Software Engineers, Applied Scientists, Data Scientists, and Product Managers

You Have:

• 1+ Years experience developing software in a professional environment

• Knowledge of data structures and algorithm fundamentals

• Experience building, testing, and managing distributed services

• Excellent coding skills in modern languages and frameworks

• Experience with AWS technologies such as ECS, Sagemaker, Redshift, Batch, DynamoDB, Lambda, SQS, and Step Functions

• Minimum of Bachelor’s degree in Computer Science or equivalent experience

Perks

• Medical, Dental, Vision & Disability Insurance

• 401(k)

• Maternity & Parental Leave

• Flexible PTO

• Amazon Employee Discount

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Job ID: TW9080

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

US, CA, San Francisco
$127,100—$185,000 USD

Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Twitch values your privacy. Please consult our Candidate Privacy Notice, for information about how we collect, use, and disclose personal information of our candidates.

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