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About the RoleJoin the Monetization ML team within Twitch's Commerce organization, where we're building the intelligent systems that power personalized experiences for creators and viewers across all monetization products. We are the team behind the ML infrastructure for ads, commerce, and money products - systems that optimize revenue and detect fraud while serving millions of users in real-time.
From production model infrastructure to API integrations across services, we're constantly pushing the boundaries of what's possible in live streaming monetization.
Our team are based in San Francisco, CA and Seattle, WA
You Will:- Build robust ML infrastructure and platforms that power personalized monetization experiences across Twitch's ecosystem
- Architect and develop APIs that seamlessly integrate ML models with existing monetization services, enabling real-time and batch predictions at scale
- Collaborate with Applied Scientists to productionize ML models, transforming research into production-ready systems that serve millions of users
- Partner with product engineering teams across monetization to deliver ML-powered features that enhance creator and viewer experiences
- Design and implement comprehensive monitoring and operational excellence systems for ML model performance, ensuring reliability and quality at scale
- Develop data ingestion and processing pipelines that support both real-time inference and batch training workflows
- Explore and build infrastructure for emerging use cases including LLM applications in monetization contexts
You Have:- 1+ years of professional software development experience with a focus on building scalable systems
- Experience building production ML infrastructure, including model deployment, serving, and monitoring systems
- Proficiency in modern programming languages (Python, Java, Go) and distributed system technologies
- A track record of building APIs and integrating systems that handle high-throughput, low-latency requirements
- Understanding of data processing pipelines and experience with streaming technologies (Flink, Kafka, or similar)
- Sharp problem-solving skills with a focus on algorithms, data structures, and distributed system design
- Bachelor's degree in Computer Science, Engineering, or equivalent real-world experience
Bonus Points- Familiarity with Twitch's tech stack: Golang, Python, Apache Flink, Cond
- Experience with workflow orchestration tools like Airflow or Conductor for managing ML pipelines
- Experience with AWS technologies like ECS, DynamoDB, Lambda, SQS, and Step Functions
- Knowledge of real-time ML serving systems and model deployment at scale
- Experience with fraud detection, recommendation systems, or monetization optimization
- A passion for gaming, streaming, or the Twitch platform
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: TW9103
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 ;br>
US, WA, Seattle - Annually
$110,500-$160,000 USD
US, CA, San Francisco - Annually
$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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