Senior Software Engineer, ML Infrastructure

Roku; Cambridge (MA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Hybrid work model

401(k)

Healthcare benefits

Job summary

Roku is seeking a Senior Software Engineer to own production ML infrastructure for the Entertainment Assistant team. You’ll drive training, evaluation, deployment, and monitoring of models, with emphasis on latency, cost, and reliability across distributed services.

You’ll collaborate with ML, product, data and platform partners to turn ambiguous problems into measurable outcomes, expanding agent-based tooling and scalable evaluation pipelines across our streaming platform.

Qualifications

• Strong production software-engineering experience, including designing, testing, operating and debugging distributed services.
• Meaningful ownership of ML infrastructure or production model delivery, with clear evidence of your contribution and its operational or adoption impact.
• A practical understanding of the ML lifecycle: training, evaluation, versioning, deployment, online validation, monitoring and safe rollback.
• Experience designing for latency, resilience, observability and cost in production systems.
• Experience with LLMs, embeddings, semantic search, retrieval or agent systems, including how you evaluate quality and control failure modes.
• Experience with caching systems and the trade-offs involved in using caching for low-latency services.
• A commitment to automation, CI/CD, code quality and evidence-led engineering decisions.
• A collaborative approach and the ability to explain technical trade-offs to partners across disciplines.
• A degree in Computer Science, Electrical Engineering or a related field, or equivalent practical experience.

Responsibilities

• Own fulfilment-ranking pipelines from training orchestration and quality gates through deployment and online validation.
• Build and operate an offline-evaluation platform, combining LLM-as-judge harnesses with deterministic checks for answer quality.
• Develop the Roku Entertainment Assistant's LLM agent, including tool routing, retrieval, guardrails and answer caching.
• Design caching as an intentional latency and cost lever for high-volume services.
• Build observability for ML and LLM systems, including latency attribution, quality metrics, tracing and per-request cost.
• Improve the reliability and operability of distributed systems, and lead the diagnosis of difficult cross-service failures.
• Drive accountable AI-assisted engineering practices across the team, building on the agents already used in release workflows.
• Work across machine-learning, product, data and platform boundaries to turn ambiguous problems into measurable delivery outcomes.

Skills

Distributed services

ML infrastructure

LLM systems

Caching systems

CI/CD

Observability

Latency optimization

Go

Python

Education

BS in CS or related field

Tools

AWS

GCP

Kubernetes

SQL

Trino/Presto

Spark

Kafka

Job description

Teamwork makes the stream work.

Roku is changing how the world watches TV

Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.

From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.

About the team

The Roku Entertainment Assistant team builds conversational AI experiences used across millions of Roku devices. The team works across fulfilment ranking, model delivery, offline and online evaluation, low-latency services, observability and product quality. Its published work includes shared model-serving and MLOps paths, automated evaluation and retraining, caching and telemetry, and agent-assisted release and operational workflows.

What is the role?

We are looking for a Senior Software Engineer with strong machine-learning infrastructure experience to help the Roku Entertainment Assistant team deliver reliable, high-quality conversational experiences at scale. You will own production systems across ranking, model delivery, evaluation and LLM-agent behaviour, working closely with machine-learning, product, data and platform partners.

This is a hands-on engineering role for someone who can move comfortably between software architecture, ML lifecycle decisions and production operations. You will improve the paths the team uses to train, evaluate, deploy and observe models, while helping us manage latency, quality and cost as the product grows.

How will I use AI at Roku?

At Roku, we don't just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We're looking for curious, adaptable builders who can show how they've used AI or automation to move faster, raise the bar, and scale their impact.

We value your AI skills if you have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you.

What will you be doing?

• Own fulfilment-ranking pipelines from training orchestration and quality gates through deployment and online validation.
• Build and operate an offline-evaluation platform, combining LLM-as-judge harnesses with deterministic checks for answer quality.
• Develop the Roku Entertainment Assistant's LLM agent, including tool routing, retrieval, guardrails and answer caching.
• Design caching as an intentional latency and cost lever for high-volume services.
• Build observability for ML and LLM systems, including latency attribution, quality metrics, tracing and per-request cost.
• Improve the reliability and operability of distributed systems, and lead the diagnosis of difficult cross-service failures.
• Drive accountable AI-assisted engineering practices across the team, building on the agents already used in release workflows.
• Work across machine-learning, product, data and platform boundaries to turn ambiguous problems into measurable delivery outcomes.

We're excited if you have

• Strong production software-engineering experience, including designing, testing, operating and debugging distributed services.
• Meaningful ownership of ML infrastructure or production model delivery, with clear evidence of your contribution and its operational or adoption impact.
• A practical understanding of the ML lifecycle: training, evaluation, versioning, deployment, online validation, monitoring and safe rollback.
• Experience designing for latency, resilience, observability and cost in production systems.
• Experience with LLMs, embeddings, semantic search, retrieval or agent systems, including how you evaluate quality and control failure modes.
• Experience with caching systems and the trade-offs involved in using caching for low-latency services.
• A commitment to automation, CI/CD, code quality and evidence-led engineering decisions.
• A collaborative approach and the ability to explain technical trade-offs to partners across disciplines.
• A degree in Computer Science, Electrical Engineering or a related field, or equivalent practical experience.

Experience with AWS or GCP, Kubernetes, SQL warehouse and batch-processing technologies such as Trino, Presto or Spark, Kafka or other streaming systems, and Go or Python would be useful. Node.js experience is a plus. We value transferable evidence over an exact match to every named technology.

#LI-MS3

What's Roku's approach to hybrid working?

Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance.

What are some of the benefits?

Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.

Accommodations

Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to [e-mail].

What should I know about Roku's culture?

Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.

We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.

To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.