About this role
Babylist builds personalization systems and foundational representations that power homepage feeds, search, and recommendations across platforms used by millions of families. Staff Machine Learning Engineers at this company own the personalization domain, deciding what to model, building custom embeddings from raw data, and overseeing the full machine learning lifecycle from orchestration to monitoring.
This role exists to guide technical direction, coach senior engineers through ambiguous challenges, and shape product roadmaps without needing direct reports. Ideal candidates bring extensive experience shipping production machine learning systems at scale, thrive in zero-to-one problem spaces, and measure success through tangible customer outcomes.
What you will do
- Take ambiguous business problems from initial sketches through to production models while measuring real customer impact.
- Build domain-specific custom embeddings from raw data that multiple product surfaces can adopt.
- Make critical modeling and architecture decisions that span multiple engineering teams.
- Own the complete machine learning lifecycle including orchestration, deployment, monitoring, and retraining loops.
- Establish standards for building personalization with artificial intelligence and design evaluation frameworks to catch errors early.
- Partner closely with product, design, and data teams to help shape what gets built from the start.
- Coach senior engineers through technical hurdles and ambiguous decision-making processes.
What you need
- Shipped production machine learning systems for multiple years with a track record of measurable impact.
- Built recommender systems or personalization features that reached real users at scale.
- Demonstrated experience changing how teams build software and systems using artificial intelligence.
- Deep familiarity with the Python machine learning ecosystem including pandas, scikit-learn, XGBoost, and PyTorch.
- Fluent across the entire machine learning lifecycle from training to orchestration and monitoring.
- Strong background in constructing custom representations directly from raw data rather than relying solely on off-the-shelf embeddings.
Benefits
- Company-paid benefits
- Target annual bonus of 20 percent of base salary
- Meaningful equity
- RRSP match
Skills and tech stack
Questions candidates ask
What is the remote work policy?
The position is remote-first across the US and Canada with team members gathering in the same room twice a year.
What is the compensation range for this role?
For a Canada-based Staff Engineer, the starting base salary ranges from $299,300 to $372,600 CAD with a target annual bonus of 20 percent of base, plus meaningful equity and an RRSP match.
What tools and technologies make up the tech stack?
The core application uses Rails, React, TypeScript, and MySQL, while machine learning relies on PyTorch, AWS SageMaker, MLflow, and custom embeddings alongside developer tooling like Claude Code and Devin.
What does the hiring process look like?
The process consists of three rounds completed in two to three weeks, starting with a recruiter conversation, followed by a one-hour language-agnostic technical screen without AI, and ending with a four-hour final round covering system design, AI-assisted coding, product sense, and values.