The opportunity
AI and machine learning are reshaping how developers debug, monitor, and ship software, and Sentry is uniquely positioned to lead that shift. We sit on a novel and massive dataset of real production errors, spans, and logs from tens of thousands of engineering organizations —…
What you'll do
Set technical direction across the team's full ML surface area: from classical models for clustering, ranking, and anomaly detection to LLM-based and agentic systems — and make sharp calls about which approach fits each problem
Define how the team evaluates and monitors ML systems in production, from: offline metrics to online experimentation to model and agent observability
Stay hands-on enough to review code and model designs, contribute to: architecture discussions, and unblock engineers on complex ML problems
Define team roadmap and deliverables, scope work, allocate resources, and: keep execution on track against ambitious goals
Partner with product managers, designers, and engineering leaders across: Sentry to identify the highest-impact opportunities for ML in our products
Foster career growth for the engineers on your team, and recruit exceptional ML talent as the team scales
What they're looking for
- + years of professional engineering experience, with significant time spent: building and shipping machine learning systems in production
- + years of engineering management experience, ideally leading ML, AI, or data-focused teams
- Familiarity with deploying and operating ML models at scale, including: evaluation, monitoring, and iteration in production
- Strong judgment in ambiguous, fast-moving environments
- Excellent written and verbal communication; comfortable working across product, research, and engineering
- A research background in machine learning, statistics, or a related field: (MS, PhD, or equivalent research experience) is a plus but not a requirement
