Software Engineer I, Monetization ML

Twitch

📍Seattle, WA
💰 $110,500 - $160,000
Posted May 21, 2026

Job Overview

Position

Software Engineer I, Monetization ML

Company

Twitch

Location

Seattle, WA

Work Type

On-site

Salary Range

$110,500 - $160,000

Job ID

li-4384756307

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
Join 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 https://amazon.jobs/en/benefits.

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.*

Interview Prep

AI-powered insights to help you prepare

Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How would you design a low-latency, high-throughput API to serve real-time ML predictions for ad targeting on Twitch?
  • 2.Describe your approach to building a data ingestion pipeline using Kafka and Flink that supports both real-time inference and batch model training.
  • 3.What strategies would you use to monitor an ML model in production that detects fraud, ensuring it maintains reliability and quality at scale?
🎯Behavioral Questions (3)
  • 1.Tell me about a time you collaborated with Applied Scientists or researchers to productionize an ML model.
  • 2.Describe a situation where you had to build or scale a system under tight latency or high throughput requirements.
  • 3.Give an example of a time you had to design a comprehensive monitoring or operational excellence system for a complex service.
🧩Situational Questions (2)
  • 1.A new LLM-based feature for monetization needs infrastructure built for it, but the applied scientists are still experimenting with the prompt and model. How do you architect the system to support their iteration while preparing for production scale?
  • 2.During a major live streaming event, the real-time ML serving API for personalized commerce experiences begins to degrade and latency spikes. What is your immediate response and troubleshooting process?

Resume Keywords

Make sure these keywords appear on your resume

ML InfrastructureReal-time ServingAPI DevelopmentApache FlinkKafkaGolangAWS ECSModel DeploymentFraud DetectionDistributed SystemsAirflowFeature Store

Interested in this position? Apply directly on LinkedIn.

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