Senior Machine Learning Engineer
About The Position
The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real-time multi-objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform that powers the entire landscape, which we continuously evolve over time. 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 aimed at improving the ad experience. We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using both general-purpose software and statistical languages.
Requirements
- Bachelors, Masters, 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 modelling environments i.e. Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
- Proficient use of AI tools and agentic coding practices
Nice To Haves
- Ad Tech experience is preferred
Responsibilities
- 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
- Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models
- Use machine learning and statistical modelling 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
- Low-level systems debugging, performance measurement, and optimisation on large production clusters
- Partner with product managers, data scientists, and other engineers to deliver impactful solutions
- Continuously learn and adapt to emerging technologies and industry trends
Benefits
- global access to mental health and financial wellness support and resources
- healthcare (medical, dental, and vision)
- life, accident, disability, commuter, and retirement options (401(k)/pension)
- time off, in accordance with local leave policies and other personal needs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
