Machine Learning Engineer
Machine Learning Engineer building statistical models, optimization systems, and experiments for mobile ad tech economics on the Revenue Engine team. Requires PhD in CS/ML/Economics and industry experience applying ML or economics at scale.
About the job
Responsibilities
- Build statistical models and production systems to balance advertiser performance with business goals.
- Tune optimization parameters, measure internal competition, and model dynamic environments.
- Design and run experiments to validate theories underpinning the mobile ad tech economy.
- Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations.
- Collaborate with a team of world-class engineers with diverse backgrounds as well as peers across the broader company (e.g. Operations, GTM).
- Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences.
- Be part of an “engineering excellence” culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review.
Requirements
- PhD in Computer Science, Machine Learning, Economics, or a related field.
- Industry experience applying economics or machine learning to large scale problems.
- Solid engineering and coding skills.
- Excellent team communication and collaboration skills.
- Experience with ad tech is a solid plus.
Compensation
- SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $235,000 - $275,000
- All other cities and towns in our approved states: $215,000 - $255,000
- Includes equity and health/vision/dental benefits.
Skills
Machine Learning, Statistics, Economics, Python, Experiment Design, Ad Tech, Optimization, Bidding Systems
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