Senior Machine Learning Engineer – Generative AI

Your mission

• Own end-to-end ML workflows: data ingestion, feature engineering, training, evaluation & production deployment

• Deep-dive into at least one core application domain: (1) price prediction; (2) two-sided market design (ranking / recommendations); (3) agentic workflows using state of the art LLMs; from prototype to robust production services.

• Establish and enforce LLMops best practices: design reproducible prompt‑engineering workflows, manage model/version tracking, automate evaluation (e.g. evals frameworks), monitor latency/cost, and refine prompts based on performance metrics.

• Set up performance tracking, alerting and automated evaluation to ensure model health in production.

• Collaborate across product, engineering and data science to translate business needs into technical solutions.

• Spar with peers in the AI team and contribute to code reviews, best practices and tooling for reproducible, production‑grade ML.

Your profile

• 5+ years of ML engineering experience, including ≥ 1 year working with LLMs

• Strong Python skills and production‑grade code practices (testing, CI/CD)

• Deep expertise in at least one of:

  • Deep learning (PyTorch, Transformers)

  • Ranking / matching algorithms

  • LLMops (RAG, evals, fine‑tuning, agentic workflows)

• Proven track record deploying containerized services at scale (Docker, Kubernetes)

• Clear communicator who bridges data science, product and engineering

• Master's/PhD in ML, CS, Statistics or related

• Passion for the craft of ML and deep learning: you love learning and keep up‑to‑date with the state of the art.

• Pride in writing clean, maintainable code.

• The customer's interest is at the center of everything you do, and you always think in their perspective.

Why us?

• Shape a product that solves real‑life problems in the construction industry

• Work in an open‑minded, collaborative, dynamic, and international team

• Fully remote team and work culture

• Freedom in your working hours. It's the results that count.

• Company off‑sites and regular team events (offline and online)

• Flexible working conditions with the possibility to do workations

• Competitive compensation, a permanent contract, and modern work equipment

• Open feedback culture with regular 1-on-1s