We're hiring an Ops Engineer to own our model-release engine, data foundations, and developer experience. You’ll create a first-class platform so every ML researcher can ship faster and more reliably. We’re looking for someone who loves automating everything, designing clean data abstractions, and seeing models roll quickly to production.
Our focus isn’t on optimizing data pipelines, we need to build the right internal tools - metadata catalogs, ML flow automation, release pipelines, and friction-free data access - that let our applied research teams iterate fast. You’ll have end-to-end ownership to design the architecture, build everything, set/enforce standards, and keep our ML team running smoothly.
Automate model release & rollback with one-click CI/CD from training artifact to deployed model, complete with versioning and validation hooks.
• Maintain MLflow (or your tool of choice) for experiment tracking, model registry, and promotion to production.
• Design a robust data catalog & metadata layer to let engineers construct the exact datasets they need by exposing consistent APIs or tools.
• Deliver clear docs, CLI / Python SDKs, and templated repos so new hires ship models in days, not weeks.
• Enforce strong practices across the team, spot bottlenecks early, and keep the tooling roadmap aligned with product goals.
• Proven ML Ops or Dev Infra experience building platforms that track, package, and ship models in production.
• Strong AWS & IaC experience – Comfortable with AWS Networking, S3, Lambda/ECS, CDK
• Fluency with experiment-tracking & model-registry tools like MLflow, Weights & Biases, SageMaker, or equivalents.
• Exceptional organization & documentation habits – You keep repos, wikis, and schemas impeccably structured so anyone can find what they need.
• Experience designing schemas and APIs that make datasets discoverable and auditable.
• Python as your first language, but you’re comfortable with C++ and lower-level languages when it helps.
• Clear bias for automation, quickly turning manual workflows into robust pipelines and tools.
Fast learners over specific backgrounds – We care more about how quickly you can pick up new skills than where you’ve worked before.
Intellectual honesty – The right answer matters more than being right. You challenge assumptions, test ideas, and pivot when needed.
Adaptability – We’re organized, but sometimes things change quickly. You find a way to make it work and balance short term deliverables with long term goals.
Ownership of outcomes – You optimize your own time, focus on what matters to deliver quickly, and cut out inefficiencies.
Not building in a vacuum – You stay connected to the rest of our teams and our customers to make sure all the pieces fit together.
Above-market salary, equity, and benefits package. In accordance with NY regulations, the salary range for this position is $100,000-$300,000 to cover a broad range of candidate experience.
Early Series A Equity
Excellent health, dental, and vision coverage
401(k) match - up to 4% of your salary
Unlimited PTO
Daily office lunches in NYC