{"id":742884,"url":"https://alion.io/job/sweatpals-senior-machine-learning-scientist","title":"Senior Machine Learning Scientist","company":{"id":685984,"name":"Sweatpals","domain":"sweatpals.com","url":"https://alion.io/company/sweatpals","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":{"label":"European time zones","utc_offset_min":0,"utc_offset_max":2},"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["DE","FR","AT","BE","BG","HR","CY","CZ","DK","FI","HU","IE","IT","NL","PL","RO","ES","SE","EE","GR","LV","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":27,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"BigQuery","optional":false},{"name":"Claude","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Machine Learning","optional":false},{"name":"PostgreSQL","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Sentence-Transformers","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"A/B Testing","optional":true},{"name":"Claude Code","optional":true},{"name":"Cursor","optional":true},{"name":"Embeddings","optional":true},{"name":"NLP","optional":true},{"name":"Python","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Rollup","optional":true},{"name":"SQL","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-05-29T17:27:27Z","employer_posted_date":"2026-05-29","last_verified_at":"2026-10-04T02:30:20Z","board_verified":true,"closed_at":null,"days_open":127,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":126},"description":"About Sweatpals\nSweatpals is the community-first fitness platform turning workouts into social experiences. Backed by a16z speedrun, Patron, Kevin Hart, Pear VC, and founders of Instacart and Dreamworks Animations, we connect hundreds of thousands of \"pals,\" hosts, and gyms through events, memberships, and social features. We're still scrappy at heart, but scaling fast.\nWe believe working out should be joyful, social, and inclusive, not just a solo grind. From run clubs and beach pilates to pickleball leagues and cold plunge socials, Sweatpals turns everyday workouts into meaningful social experiences.\nSweatpals also gives local leaders the tools to grow their fitness communities from side hustles to full-time, even million-dollar businesses. Hosts use our platform to run their business, from ticketing and memberships to marketing tools.\nWe're an AI-forward company. If you're excited about working at the intersection of ML, product, and a real marketplace, you'll fit right in.\nThe Role\nWe're looking for a Senior Machine Learning Scientist to join the AI Squad and own the most ambitious ML work on our roadmap. You'll report to the Head of AI and partner closely with engineering and product to ship models that move our marketplace.\nThis is a high-ownership role. You'll define problems, run the science, ship to production, and measure real user impact. You won't inherit a graveyard of half-finished notebooks. You'll build the next layer of ML at Sweatpals on top of what we've already shipped: semantic search, event tagging, collection ranking, retention models, and our LLM-powered HostCopilot and Front Desk Agent.\nYou'll spend your time on problems like:\nHow do we rank events for each Pal so they discover more hosts they'd love?\n\nCan we predict churn early enough for HostCopilot to nudge before it happens?\n\nWhat's the right way to price a class or membership to maximize host GMV without hurting bookings?\n\nHow do we make LLMs reliable enough to draft host campaigns, recommend events, and answer questions at a real front desk?\n\nHow do we measure if our models actually move the marketplace, not just CTR?\n\nWhat You'll Do\nModeling & Research\nFrame fuzzy product problems as ML problems and pick the right approach: ranking, retrieval, classification, sequence models, LLM agents, or classic stats\n\nRun end-to-end: data exploration, offline evaluation, prototype, online experiment, iteration\n\nPush to the cutting edge when it matters, stay pragmatic when it doesn't\n\nOwn offline metrics (NDCG, recall@k, AUC, calibration) and tie them to online metrics (booking lift, retention, GMV)\n\nProduction & Shipping\nShip 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)\n\nBuild evaluation harnesses and monitoring so we know when models drift\n\nKeep latency budgets honest\n\nLLM & Agent Systems\nDevelop LLM-powered features across HostCopilot (drip campaigns, retention nudges, pricing and content suggestions) and Pal-facing surfaces (AI Concierge, semantic search, recommendations)\n\nBuild agentic systems with tool use, RAG, structured outputs, evaluation loops, and human-in-the-loop where needed\n\nDecide when to prompt-engineer, when to fine-tune, and when a classical model is the better answer\n\nCross-Functional Impact\nPartner with product to size opportunities and translate findings into roadmap decisions\n\nPartner with growth and our data analyst to measure marketplace impact rigorously\n\nSet the bar for the squad on ML rigor: offline evaluation, experiment design, and writeups\n\nWhat We're Looking For\nExperience\n5+ years of applied ML experience shipping models to production. Bonus if some of that was in marketplaces, search, or recommendations\n\nTrack record of taking a problem from \"vague PM ask\" to \"shipped feature that moved a metric\"\n\nComfort with the full lifecycle: framing, data, modeling, evaluation, deployment, monitoring\n\nTechnical Skills\nStrong Python and SQL. You write production code, not just notebooks\n\nSolid foundations in at least one ML area: ranking and recommendation systems, NLP and embeddings, classical ML, LLMs and agents, or causal inference\n\nComfortable with modern LLM tooling: prompting, RAG, evaluation, tool use, structured outputs\n\nPractical stats: experiment design, dealing with confounding, knowing when an A/B test is broken\n\nFamiliarity with our stack is a plus: FastAPI, PostgreSQL, BigQuery, FAISS, sentence-transformers, AWS, Amplitude\n\nAdvanced degree in ML, CS, stats, or a related field is typical. PhD or research background is a strong bonus\n\nMindset\nProduct first. You care about user impact more than novelty\n\nYou use AI tools daily. Claude Code, Cursor, whatever ships faster\n\nYou write things down. Memos, experiment results, design docs\n\nYou're comfortable being the second dedicated ML person at the company and pushing the bar up\n\nYou care about quality and follow through. You don't ship and forget\n\nWhy Join\nOwnership: You'll define the next chapter of ML at Sweatpals, not maintain someone else's models\n\nAI-native culture: We use Claude Code daily, ship fast, and treat AI tooling as table stakes\n\nFlexibility: Remote-first, async-friendly, EU timezone\n\nCompensation: Competitive salary plus early-stage equity\n\nOur Values\nCelebrate Diversity of Thought: We embrace different backgrounds, opinions, and ways of thinking. We don't just welcome disagreement, we believe it makes the product better.\n\nBe a Leader: We take initiative, speak up, and drive things forward, no matter your title. Leadership is a mindset, not a level.\n\nRoll Up Our Sleeves: We do what it takes. No job is too small when we're building something big.\n\nEmbrace Adventure: We stay curious, push boundaries, and see challenges as opportunities. Startups are a rollercoaster and we're here for the ride.\n\nMake Excellence the Baseline: We hold a high bar for quality and follow through. Doing great work is the starting point, not the finish line.\n\nWe're still early, which means your work will shape our path and our impact on communities and businesses everywhere. If you're excited by challenge, autonomy, and building something that matters, you'll feel at home here.\nHow to Apply\nSend your resume (or LinkedIn) and a short note answering:\nOne ML system you shipped end-to-end and what it actually changed\n\nA modeling decision you made that turned out to be wrong, and what you learned\n\nA paper, blog post, or repo you keep going back to (optional, but we love this)","description_format":"text","description_chars":6583,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"Austria","iso":"AT","kind":"region"},{"name":"Belgium","iso":"BE","kind":"region"},{"name":"Bulgaria","iso":"BG","kind":"region"},{"name":"Croatia","iso":"HR","kind":"region"},{"name":"Cyprus","iso":"CY","kind":"region"},{"name":"Czech Republic","iso":"CZ","kind":"region"},{"name":"Denmark","iso":"DK","kind":"region"},{"name":"Finland","iso":"FI","kind":"region"},{"name":"Hungary","iso":"HU","kind":"region"},{"name":"Ireland","iso":"IE","kind":"region"},{"name":"Italy","iso":"IT","kind":"region"},{"name":"Netherlands","iso":"NL","kind":"region"},{"name":"Poland","iso":"PL","kind":"region"},{"name":"Romania","iso":"RO","kind":"region"},{"name":"Spain","iso":"ES","kind":"region"},{"name":"Sweden","iso":"SE","kind":"region"},{"name":"Estonia","iso":"EE","kind":"region"},{"name":"Greece","iso":"GR","kind":"region"},{"name":"Latvia","iso":"LV","kind":"region"},{"name":"Lithuania","iso":"LT","kind":"region"},{"name":"Luxembourg","iso":"LU","kind":"region"},{"name":"Malta","iso":"MT","kind":"region"},{"name":"Portugal","iso":"PT","kind":"region"},{"name":"Slovakia","iso":"SK","kind":"region"},{"name":"Slovenia","iso":"SI","kind":"region"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fitness"],"lifecycle":[{"event":"open","at":"2026-09-11T13:11:44Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.398,"p_room":0.28,"age_days":126,"expected_fill_days":39,"reasons":["conf:21","win:tail","crowd:"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/sweatpals-senior-machine-learning-scientist","json_url":"https://alion.io/job/sweatpals-senior-machine-learning-scientist.json","meta":{"generated_at":"2026-10-04T02:32:35Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3693,"day_limit":5000,"remaining_today":1307,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}