Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Statistics @ 1
Machine Learning @ 3
Communication @ 3
Experimentation @ 3
Engineering Management @ 5
LLM @ 3
Sentry @ 3
Observability @ 3
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About Sentry
Bad software is everywhere, and we’re tired of it. Sentry is on a mission to help developers write better software faster so we can get back to enjoying technology.
With more than $217 million in funding and 100,000+ organizations that believe we’re on to something, we're building performance and error monitoring tools that help companies like Disney, Microsoft, and Atlassian spend less time fixing bugs and more time building products.
Sentry embraces a hybrid work model across our global hubs, with Mondays, Tuesdays, and Thursdays set as in-office anchor days to encourage meaningful collaboration.
About the role
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 — the kind of signal that makes ML genuinely useful, whether it's a clustering model that groups related issues, a ranking system that surfaces the right alert at the right time, or an agent that proposes a fix.
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.
Responsibilities
- 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
Requirements
- 8+ years of professional engineering experience, with significant time spent building and shipping machine learning systems in production
- 3+ 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
Why you'll love this role
- You will shape how AI and developer tools come together, and define how engineers and coding agents collaborate to find and fix problems
- The ML team is early-stage with plenty of greenfield work to shape
- High-impact, high-visibility projects with cross-functional collaboration across product, design, and engineering
- Opportunity to grow engineers and recruit top ML talent
Compensation
The base salary range that Sentry reasonably expects to pay for this position is $220,000 to $280,000. A successful candidate's actual base salary amount will be determined by factors including work location, education, experience, skills, and job-related knowledge.
Benefits
A successful candidate will be eligible to participate in Sentry's employee benefit plans/programs applicable to the candidate's position (including incentive compensation, equity grants, paid time off, and group health insurance coverage).
Equal Opportunity at Sentry
Sentry is committed to providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This includes providing reasonable accommodations for candidates or employees with disabilities. If you need assistance or an accommodation due to a disability, contact [email protected].