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.
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
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 Uber Eats & Uber home when working late
The most beautiful office space and work environment in Berlin
Hybrid (minimum three days in the office)
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