The ad says“3+ years of engineering management experience, ideally leading ML, AI, or data-focused teams”
The ad says“Familiarity with deploying and operating ML models at scale, including evaluation, monitoring, and iteration in production”
The ad says“8+ years of professional engineering experience, with significant time spent building and shipping machine learning systems in production”
The ad says“Have a strong ML engineering background that you use to inform and validate the team’s technical decisions, and you’re comfortable staying close to the code”
We’re looking for an Engineering Manager to lead and grow our Machine Learning Engineering team
This team owns the full spectrum of ML at Sentry: classical techniques like clustering, ranking, anomaly detection, and embeddings that quietly power core product surfaces today, alongside the LLM-based and agentic systems shaping where the product is headed
You’ll partner closely with product, design, and engineering leaders to decide where ML belongs in our products, what kind of ML actually fits the problem, and how we translate that work into experiences millions of developers rely on every day
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
Benefits
Competitive Compensation + Equity
Medical, Dental, Vision Insurance
Commuter Stipend
Professional Development Stipend
Health & Wellness Benefits
Charitable Matching Program
Flexible PTO
Paid Parental Leave
401k Plan
Preferred experience
Thrive in cross-functional environments and enjoy collaborating across product, design, and engineering to ship great work
Excellent written and verbal communication; comfortable working across product, research, and engineering
Not sure if you meet 100% of the qualifications? We encourage you to apply anyway. We’re interested in people who are excited about this opportunity and eager to grow
Are excited to shape how AI and developer tools come together, and want to define how engineers and coding agents collaborate to find and fix problems
3+ years of engineering management experience, ideally leading ML, AI, or data-focused teams
8+ years of professional engineering experience, with significant time spent building and shipping machine learning systems in production
Strong judgment in ambiguous, fast-moving environments
Have a strong ML engineering background that you use to inform and validate the team’s technical decisions, and you’re comfortable staying close to the code
Are driven by impact and want to lead a team working on high-stakes, high-visibility projects
Love building things from the ground up — the ML team is still in its early chapters, and there’s plenty of greenfield to shape
Care deeply about growing the engineers around you and finding opportunities for them to do the best work of their careers
A research background in machine learning, statistics, or a related field (MS, PhD, or equivalent research experience) is a plus but not a requirement
Familiarity with deploying and operating ML models at scale, including evaluation, monitoring, and iteration in production
