Machine Learning/ AI Engineer in Berlin
HeuteBerlin
Vollzeit
80.000 € - 110.000 € / Jahr (laut Jobangabe)
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Geschätztes Gehalt
Das könntest du laut kununu User:innen als Data Scientist in Deutschland verdienen
Ø 67.300 €
Bruttodurchschnittsgehalt Vollzeit
48.000 €99.000 €
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Was die Firma über den Job sagt
About us
At Match on Monday, we specialize in placing highly qualified IT professionals. For one of our renowned clients in the digital innovation space, we are currently looking for a Python Backend Engineer in Berlin. Our client is developing a B2B Software-as-a-Service (SaaS) product in the AI field.
Tasks
Build and iterate on text-based generative AI applications end-to-end (from idea to prototype to production)
Run systematic benchmarking and experimentation across models, prompts, and system designs
Develop and improve ML components that discover, structure, and retrieve knowledge effectively
Design evaluation frameworks to measure quality, factuality, and reliability of model outputs
Collaborate with product and engineering to translate real-world needs into scalable ML solutions
Contribute to advanced initiatives such as synthetic data generation, model distillation, and embedding/retrieval improvements
Profile
Strong applied ML background with hands-on experience shipping ML-powered features
Python development experience and solid software engineering fundamentals
Familiarity with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow, etc.)
Comfortable explaining core ML concepts (transformers, embeddings, experimentation workflows)
Experience scaling ML systems to large datasets and production environments
Bonus: background in NLP, reinforcement learning, or life sciences / biotech domains
Bonus: familiarity with cloud/infra tooling (Docker, CI/CD, model serving, data processing)
Comfortable working in a fast-paced environment with high ownership and ambiguity
We offfer
High-impact, mission-driven work applying AI to real-world information challenges
Competitive salary and meaningful equity/ownership options
Learning & development budget (books, courses, conferences)
Fast-growth environment with opportunities to shape both product and platform early
Collaborative team culture with ambitious, curious colleagues
Regular team retreats to connect, collaborate, and have fun