Senior Machine Learning Scientist

🕒 5 days ago

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SweatPals

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🛍️ eCommerce

🧘 Wellness

⚽ Sports

eCommerce • Wellness • Sports

SweatPals is a platform designed to enhance fitness events and community management by offering tools for creating, managing, and monetizing events seamlessly. It provides features such as automated waivers, tailored questionnaires, customizable landing pages, mobile check-in, and marketing support to attract and engage audiences. With dynamic membership plans, payment automation, and powerful insights into member preferences, SweatPals helps fitness enthusiasts and organizers build and engage their communities effectively.

📋 Description

• Frame fuzzy product problems as ML problems and pick the right approach: ranking, retrieval, classification, sequence models, LLM agents, or classic stats • Run end-to-end: data exploration, offline evaluation, prototype, online experiment, iteration • Push to the cutting edge when it matters, stay pragmatic when it doesn't • Own offline metrics (NDCG, recall@k, AUC, calibration) and tie them to online metrics (booking lift, retention, GMV) • Ship models to production with our engineering team. Our ML stack is FastAPI, PostgreSQL, BigQuery, AWS App Runner, with retrieval via FAISS and sentence-transformers, and managed LLM APIs (Claude, Gemini) • Build evaluation harnesses and monitoring so we know when models drift • Develop LLM-powered features across HostCopilot (drip campaigns, retention nudges, pricing and content suggestions) and Pal-facing surfaces (AI Concierge, semantic search, recommendations) • Partner with product to size opportunities and translate findings into roadmap decisions • Set the bar for the squad on ML rigor: offline evaluation, experiment design, and writeups

🎯 Requirements

• 5+ years of applied ML experience shipping models to production. Bonus if some of that was in marketplaces, search, or recommendations • Track record of taking a problem from "vague PM ask" to "shipped feature that moved a metric" • Comfort with the full lifecycle: framing, data, modeling, evaluation, deployment, monitoring • Strong Python and SQL. You write production code, not just notebooks • Solid foundations in at least one ML area: ranking and recommendation systems, NLP and embeddings, classical ML, LLMs and agents, or causal inference • Comfortable with modern LLM tooling: prompting, RAG, evaluation, tool use, structured outputs • Practical stats: experiment design, dealing with confounding, knowing when an A/B test is broken • Familiarity with our stack is a plus: FastAPI, PostgreSQL, BigQuery, FAISS, sentence-transformers, AWS, Amplitude • Advanced degree in ML, CS, stats, or a related field is typical. PhD or research background is a strong bonus

🏖️ Benefits

• Ownership: You'll define the next chapter of ML at Sweatpals, not maintain someone else's models • AI-native culture: We use Claude Code daily, ship fast, and treat AI tooling as table stakes • Flexibility: Remote-first, async-friendly, EU timezone • Compensation: Competitive salary plus early-stage equity