Job Description
What you’ll do
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Train, test, and ship models that power Peec AI’s recommendations - helping customers boost their visibility in AI search
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Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility
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Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems
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Design and implement data pipelines to ingest, process, and analyze large volumes of data
What we’re looking for
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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)
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Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
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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
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Excellent communication skills with the ability to explain complex technical concepts to customers and stakeholders
Our Data Science Stack
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Languages: Python, SQL
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Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
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Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
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AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc.
Bonus Points
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Contributions to open-source projects
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Deployed side/hobby projects that we can check out
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Presented research papers at top ML or AI conferences
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Having started a company before or worked at a high-growth startup
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Fluency in Typescript
What we offer
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Exciting and challenging work with real impact and ownership at one of Europe’s fastest-growing Series A startups
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Aggressive equity compensation package
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Remote working (applicants must be located within ±3 hours of the Berlin (CET) time)
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