Senior Machine Learning Engineer

About the role

We’re on a mission to build cutting-edge advertising technology that empowers businesses to run sustainable and highly profitable campaigns. The Ad Performance team owns server technologies, data, and cloud services designed to improve the ad experience. We're looking for seasoned engineers with machine learning backgrounds to support this mission.

Responsibilities

• ML infrastructure: Help build a first-class machine learning platform from the ground up, which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality
• Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models
• Model training with batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy
• Production operations: Low-level systems debugging, performance measurement, and optimization on large production clusters
• Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions
• Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Statistics, or a related field
• 5 years of experience in applied machine learning on real use cases
• Proficient coding skills and strong software development experience in Spark, Python, or Java
• Familiarity with real-time evaluation of models with low latency constraints
• Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
• Ability to work with large-scale computing frameworks, data analysis systems, and modeling environments i.e., Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
• Ad Tech experience is preferred
• Proficient use of AI tools and agentic coding practices

Qualifications

• Experience with real-time evaluation of models with low latency constraints
• Experience with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
• Experience working with large-scale computing frameworks, data analysis systems, and modeling environments i.e., Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
• Experience with AI tools and agentic coding practices

Skills

• Machine Learning
• Statistical Modeling
• Real-Time Evaluation
• Distributed ML Frameworks
• Large-Scale Computing
• AI Tools
• Agentic Coding Practices

Benefits

• Health Insurance
• Equity Awards
• Life Insurance
• Disability Benefits
• Parental Leave
• Wellness Benefits
• Paid Time Off

Pay

The estimated annual salary for this position is between $229,500 - $367,100 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location.

Schedule

Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.