Responsibilities
- Data Analysis / Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models.
- Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system performance, quality and accuracy.
- Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads.
- ML Infrastructure: Help build a first-class machine learning platform from the ground up which helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality.
- Low-Level Systems Debugging, Performance Measurement & Optimisation: Performance measurement and optimisation on large production clusters.
Requirements
- First-hand experience in applied machine learning on real recommendations use cases.
- Experience with ML/distributed ML frameworks like Ray, Spark-MLlib, TensorFlow etc.
- Experience with real-time scoring/evaluation of models with low latency constraints.
- Great coding skills and strong software development experience (we use Spark, Python and Java a lot).
- Ability to work with large-scale computing frameworks, data analysis systems and modelling environments. Examples include technologies like Spark, Hive, NoSQL stores etc.
- Bachelor’s, Master’s or PhD in Computer Science, Statistics or a related field.
Nice to Have
- Brownie points for productionised sequential learning use cases!
- Ad-tech/Mar-tech background is a plus.
Benefits
- 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.
Work Arrangement
Hybrid
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 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 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.
