Peec
Data Scientist
2w ago
100000 –150000 EUR / yearEuropepythonfastapidockergcpsqlpandasnumpypytorch+1
Develop and deploy AI-driven data models and algorithms to enhance brand visibility in AI search, collaborating closely with engineering teams.
Nice to have
- Contributions to open-source projects
- Deployed side/hobby projects that we can check out
- Presented research papers at top ML or AI conferences
- Having started a company before or worked at a high-growth startup
- Fluency in Typescript
Conditions
- Exciting and challenging work with real impact and ownership at one of Europe’s fastest-growing Series A startups
- Regular team events and off-sites
- Aggressive equity compensation package
- Paid Dinner & Uber home when working late
- The most beautiful office space and work environment in Berlin
Other
- Train, test, and ship models that power Peec AI’s recommendations - helping customers boost their visibility in AI search
- Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility
- Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems
- Design and implement data pipelines to ingest, process, and analyze large volumes of data
- Proven backend development skills in Python with experience building APIs, data pipelines, or ML infrastructure, and familiarity with tools like FastAPI, Docker, and cloud platforms (preferably GCP)
- Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
- Track record of taking projects from research to production in a fast-moving startup environment, with strong problem-solving skills and comfort working with ambiguous, evolving problems
- Excellent communication skills with the ability to explain complex technical concepts to customers and stakeholders
- Languages : Python, SQL
- Libraries : Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
- Backend : GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
- AI Models : OpenAI, Claude, Perplexity, Gemini, Llama, etc.