Senior Machine Learning Scientist

This is a fully remote position, open to applicants in Europe.

📋 Description

• Translate ambiguous product challenges into machine learning problems and select the appropriate methodologies: ranking, retrieval, classification, sequence models, LLM agents, or traditional statistics.

• Manage the entire process from data exploration and offline evaluation to prototyping, conducting online experiments, and iterating on results.

• Embrace innovative solutions when necessary while maintaining a practical approach when appropriate.

• Take responsibility for offline metrics (NDCG, recall@k, AUC, calibration) and link them to online performance indicators (booking lift, retention, GMV).

• Collaborate with our engineering team to deploy models into production. Our machine learning stack includes FastAPI, PostgreSQL, BigQuery, AWS App Runner, with retrieval systems utilizing FAISS and sentence-transformers, along with managed LLM APIs (Claude, Gemini).

• Create evaluation frameworks and monitoring systems to detect model drift.

• Develop LLM-enhanced features across HostCopilot (such as drip campaigns, retention nudges, pricing, and content suggestions) and Pal-facing interfaces (AI Concierge, semantic search, recommendations).

• Work alongside product teams to assess opportunities and convert insights into actionable roadmap decisions.

• Establish high standards for the team regarding machine learning rigor: offline evaluations, experiment design, and documentation.

⛳️ Requirements

• A minimum of 5 years of hands-on machine learning experience with a proven track record of deploying models in production. Experience in marketplaces, search, or recommendation systems is a plus.

• Demonstrated ability to transform a "vague product manager request" into a "shipped feature that positively impacted a metric."

• Familiarity with the complete lifecycle: problem framing, data handling, modeling, evaluation, deployment, and monitoring.

• Proficient in Python and SQL; you produce production-ready code beyond just notebook scripts.

• Solid grounding in at least one machine learning domain: ranking and recommendation systems, natural language processing and embeddings, classical machine learning, LLMs and agents, or causal inference.

• Comfortable utilizing modern LLM tools: prompting, retrieval-augmented generation, evaluation techniques, tool utilization, and structured outputs.

• Knowledgeable in practical statistics: experiment design, addressing confounding variables, and recognizing when an A/B test is compromised.

• Familiarity with our technology stack is advantageous: FastAPI, PostgreSQL, BigQuery, FAISS, sentence-transformers, AWS, Amplitude.

• An advanced degree in machine learning, computer science, statistics, or a related discipline is typical; a PhD or research background is a significant asset.

🏝️ Benefits

• Ownership: You will have the opportunity to shape the future of machine learning at Sweatpals rather than just maintain existing models.

• AI-native culture: We integrate Claude Code into our daily operations, prioritize rapid deployment, and consider AI tools as essential.

• Flexibility: Enjoy a remote-first, asynchronous-friendly environment aligned with EU time zones.

• Compensation: Receive a competitive salary along with equity in an early-stage company.