Babylist - Staff Machine Learning Engineer
Requirements
• You've shipped production ML for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You've already changed how a team builds with AI, and the new way stuck. • You've built recommender systems or personalization that reached real users at scale, and you can point to what moved because of it. You're deep in the Python ML ecosystem (pandas, scikit-learn, XGBoost, PyTorch) and fluent across the whole lifecycle, from orchestration to monitoring, not just training. The thing that sets you apart: you build custom representations from raw data instead of reaching for the off-the-shelf embedding. • A few things that tend to be true of people who thrive here: • You measure yourself by impact: a customer outcome, or a model a dozen surfaces come to depend on. • You go zero-to-one: define the problem space, architect from scratch and own it end to end. • You're curious: you spot problems before they're filed and push your own ideas until they ship.
Responsibilities
• Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. • Make the modeling and architecture calls that span surfaces and are expensive to reverse. • Design the evaluation, offline and online, that tells us a model is good before and after it ships. • Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. • Partner with product, design and data to help shape what's worth building. • Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Benefits
• We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. • How We Build • AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. • The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. • The Stack • Core app: Rails, Packwerk, React, TypeScript, Sidekiq • Core app: • Mobile: iOS (Swift), Android (Kotlin) • Mobile: • Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma • Data, search & events: • Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow • Machine learning: • AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim • AI & dev tooling: • Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly • Infra & ops: • Key integrations: Shopify (payments), Iterable (CRM) • Key integrations: • An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. • Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. • How We Work • Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. • How We Hire • Three rounds, usually two to three weeks start to finish. • Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. • Recruiter conversation (30 minutes). • Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. • Technical screen (1 hour). • Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. • Final round (4 hours). • If your timeline is tight, tell us and we'll move faster. • Company-paid medical and fully covered dental and vision • Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program • Winter Wonder Week, a paid company-wide week off at the end of the year • A remote-work stipend • Mental-health and wellness support • A Few Things To Know • We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. • We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. • If you have a family member or close relationship with a Babylist employee, let your recruiter know. • Official outreach only ever comes from an @babylist.com address
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