Senior Staff Machine Learning Engineer, Ads Ranking
New
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RedditOnline advertising
Listing locations: USA; 100% remote opportunityFull-TimeStaff
SalaryThe base salary range for this position is: $292,500 — $409,500 USD. This job is eligible to receive equity in the form of restricted stock units.
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Job Details
- Experience
- 9+ years of experience in ML engineering, applied ML, or a related field
- Required Skills
- PythonMachine Learning
Requirements
- Have 9+ years of experience in ML engineering, applied ML, or a related field, with substantial production impact.
- Bring Senior Staff-level technical leadership and a record of influencing direction across teams.
- Demonstrate deep modeling expertise and strong fundamentals in data, objectives, architectures, optimization, evaluation, and experimentation.
- Provide concrete examples of using agentic AI or AI coding tools to produce better ML outcomes, not just faster code generation.
- Be able to design guardrails and evaluations that make autonomous or semi-autonomous workflows trustworthy.
- Have strong coding ability in Python.
- Be fluent with modern ML frameworks and data tooling.
- Bring clear, concise communication and a collaborative, low-ego approach to technical leadership.
Responsibilities
- Develop advanced machine learning models and agentic workflows that help teams design, train, evaluate, and improve models.
- Use AI-assisted development systems such as Claude and Cursor to investigate model behavior, generate and test hypotheses, automate analysis, and improve code and experiments.
- Build reliable loops for data and label analysis, feature and embedding development, architecture comparison, hyperparameter optimization, error analysis, and experiment readouts.
- Design evaluation harnesses to measure model outcomes and agent or workflow quality, including correctness, reproducibility, regressions, cost, and latency.
- Partner with product, data science, ML infrastructure, and engineering teams to connect modeling improvements to user and business outcomes.
- Set technical direction across teams, mentor engineers, and raise the bar for modeling rigor and AI-assisted engineering.
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