Senior Machine Learning Scientist
Sweatpals · Remote · Remote · Europe ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior ML Scientist
- Fully remote (EU timezone)
- Python + SQL + LLMs
- Marketplace & Recommendations
- High ownership role
Join the AI Squad at Sweatpals, a community-first fitness platform backed by prominent investors. You will own ambitious machine learning projects, from event ranking to LLM-powered host tools, working closely with engineering and product teams to ship models that drive marketplace impact.
What you'll do
- Frame product challenges as ML problems using ranking, retrieval, or LLM agents
- Manage end-to-end model lifecycle from data exploration to online experiments
- Ship models to production using FastAPI, AWS, and managed LLM APIs
- Develop LLM-powered features for host retention and user recommendations
- Build evaluation harnesses and monitoring systems to detect model drift
- Partner with product and growth teams to measure marketplace impact rigorously
What you'll need
- 5+ years of applied ML experience shipping models to production
- Strong proficiency in Python and SQL for writing production code
- Solid foundation in ranking, NLP, classical ML, or causal inference
- Experience with modern LLM tooling including prompting and RAG
- Practical knowledge of experiment design and statistical analysis
- Track record of translating vague requirements into shipped features
Nice to have
- Experience in marketplaces, search, or recommendation systems
- Familiarity with FastAPI, PostgreSQL, BigQuery, and FAISS
- Advanced degree in ML, Computer Science, or Statistics
- PhD or prior research background
Stack
- Python
- SQL
- FastAPI
- PostgreSQL
- BigQuery
- AWS App Runner
- FAISS
- sentence-transformers
- Claude
- Gemini
How you'll work
- Remote-first culture
- Async-friendly workflow
- EU timezone required
What you get
- Competitive salary
- Early-stage equity
- High ownership and autonomy
- AI-native culture with daily AI tool usage
Hiring process
- Submit resume or LinkedIn profile
- Include note on an end-to-end ML system you shipped
- Describe a modeling decision that failed and lessons learned
- Optionally share a relevant paper, blog post, or repository