ml engineer for construction marketplaces

Wave Group is a fast-growing B2B SaaS business digitising a historically manual, paper-heavy construction industry. Its marketplace connects two sides of the industry, while machine learning supports pricing, matching, and agentic workflow automation.

• Take models from idea to production by designing, training, evaluating, deploying, and iterating on them end to end;
• Improve models that help customers evaluate bids and make procurement decisions using millions of price data points;
• Iterate on ranking, search, and retrieval systems that match subcontractors with tenders;
• Design offline evaluations, run online A/B tests, and drive metrics-led iteration;
• Build and improve agentic systems that orchestrate multi-step reasoning across the tendering workflow;
• Ship models into the product through backend services, APIs, and integration with the TypeScript web app;
• Maintain production ML and AI systems through monitoring, alerting, and continuous improvement.

• 4–5 Years of experience building, training, and shipping production ML models, including classical ML and deep learning;
• Fluent in a modern ML framework, ideally PyTorch;
• Experience building ranking, search, recommendation, or price prediction systems;
• Strong Python and production-grade coding skills;
• Hands-on experience building and deploying LLM and agent systems, including RAG, tool use, multi-step reasoning, and evaluations;
• Experience with offline metrics and online A/B testing;
• End-to-end product delivery experience, from research code to shipped features;
• Product mindset and ability to shape what gets built;
• Nice to have: German, TypeScript/React/Node, embedding models, fine-tuning, model training at scale, construction, procurement or marketplace experience, GCP or AWS ML infrastructure, startup or high-ownership experience.

• Equity equal to 100% of salary, vesting over 4 years;
• Fully remote anywhere in Europe, with proximity to Berlin preferred;
• Visa sponsorship is not available; candidates need the right to work in their country of residence.