Senior Machine Learning Engineer, Moloco NEXT
MOLOCO — Menlo Park
- Company: MOLOCO
- Location: Menlo Park
- Salary: $200k - $260k
- Work model: On-site
- Category: Data Science
- Experience: Senior (6+yr)
- Timezone: Any timezone (fully async)
- Posted: 2026-07-29
Tags: Data Scientist, full-time, Actively Hiring, Top Responder, Quick Responder, B2b
Job description
The Impact You’ll Be Contributing to Moloco:
Moloco NEXT is Moloco's performance advertising platform within Moloco. As a Senior Machine Learning Engineer on NEXT, you'll own the CTR/CVR prediction models inside a real-time bidding system that decides on every ad request in under 100ms.
The Opportunity:
- Own a production CTR/CVR prediction model end-to-end — modeling, eval, feature pipelines, online experimentation, and post-launch ops. By month six, you'll own a meaningful slice of NEXT's ML stack.
- Hunt for the missing signals that move the needle: new data sources to log and ingest, derived and contextual features the current model doesn't yet see. On NEXT, most wins come from finding signals others missed — not from architectural cleverness.
- Run the loop fast: design offline evaluation, ship to online A/B, read out in days, iterate. Diagnose the offline-online divergences when they show up — and they will.
- Build the agentic tooling that automates parts of our experiment-debugging and signal-discovery workflow, both as a contributor and as a user.
- Set technical direction. Decide what NEXT should bet on next quarter, not just execute on assignments. Bridge to the data and pipeline teams whose signals feed our models — most signal-hunting wins depend on getting those teams aligned.
- Embrace the unglamorous parts: data-quality instrumentation, train/serve consistency in feature pipelines, slicing eval to find failure modes, and the careful experiment debugging that separates real wins from noise.
How Do I Know if the Role is Right For Me?
- 5+ years of machine learning experience with a track record of shipping production-grade models in business-critical environments. We don't filter on degrees.
- Experience with data analysis
- Experience working on large-scale prediction or decisioning systems — CTR/CVR, ranking, recommendation, personalization, or related.
- Experience writing code in Python
- Comfortable functioning under ambiguity
- Bonus: experience using LLMs as agents or feature extractors — especially in evaluation, experiment debugging, or signal-discovery contexts.