Engineering Manager (Data Science)
Peec AI
Berlin, Germany
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Intermediate Compensation
€ 160KJob location
Berlin, Germany
Tech stack
API
Artificial Intelligence
Google BigQuery
Cloud Computing
Data Infrastructure
Python
PostgreSQL
Machine Learning
NumPy
TensorFlow
Standard Sql
Reverse Engineering
Search Technologies
Software Deployment
PyTorch
Large Language Models
Backend
FastAPI
Pandas
ONNX (Open Neural Network Exchange) Format
HuggingFace
Machine Learning Operations
Data Pipelines
Docker
Job description
- Build, mentor, and lead an elite data science team as a trusted, empathetic player-coach, while clearly communicating complex technical ideas to executives, customers, and partners
- Personally design, train, deploy, and own the models that power Peec AI's AI Search recommendations, taking hands-on responsibility for our most business-critical ML systems
- Develop and ship novel algorithms that reverse-engineer AI search and LLM behavior, turning deep technical insight into durable, customer-facing product advantages
- Own the full ML lifecycle end-to-end - from first-principles research and rigorous experimentation to production deployment, monitoring, and continuous improvement
- Architect and evolve scalable data and ML systems, making high-leverage decisions across data pipelines, modeling approaches, evaluation frameworks, and model serving
- Write and review production-grade code at an exceptional standard, setting the technical bar for the entire organization
Requirements
- 8+ years of professional data science experience, with at least 3+ years in a leadership or managerial role at a top-tier high growth startup, or FAANG level tech company (e.g., Tech Lead, EM, SDM)
- A world-class data science leader with a rare combination of deep technical mastery and proven leadership, who has built and shipped category-defining ML products in high-growth or frontier environments
- A demonstrable history of personally owning and scaling complex ML systems from raw research ideas to reliable, high-impact production deployments
- Exceptional command of Python and applied machine learning, with strong systems-level instincts spanning APIs, data pipelines, ML infrastructure, and production reliability
- A deep, first-principles understanding of LLMs and AI search systems, including the ability to rigorously evaluate, reverse-engineer, and reason about emergent model behavior
- Experience making consequential architectural and modeling decisions in cloud-native environments (preferably GCP), using tools like FastAPI, Docker, and modern data platforms
- Outstanding judgment, communication, and problem-solving ability, with the credibility to set direction, earn trust, and lead through extreme ambiguity
Our Data Science Stack
- 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, and others
Benefits & conditions
Bonus Points
- Widely recognized contributions to open-source projects or foundational ML tooling
- Publicly visible side or research projects demonstrating exceptional technical depth
- Publications or talks at top-tier ML or AI conferences
- Founder experience or senior technical leadership in high-growth startups
- Fluency in TypeScript
What we offer
- A defining leadership role with 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