Posted today · be early
Senior Data Scientist (m/f/x)
Makersite
WorldwideremotePosted today
Skill Required
AI-EngineeringMachine-Learning-EngineeringLLMOpsData-ScienceData-ScientistSenior-Data-Scientist-IIISenior-Data-ScienceSenior-Machine-Learning-Data-ScientistSenior-Data-Scientist-LeadSenior-Data-Science-SpecialistData Scientistsoftware engineeringGenerative AIGitHub ActionsObservabilityCD pipelinesLangChainPrototypingEngineeringKubernetesdesigningbuildingRAGFastAPIGraphQLTestNGPythonMLflowDockerdesignGitOpenAPIAzureCI/CDCloudDesign PatternsFulltime
Key highlights
- 30 Days Paid Time Off
- Remote-First Flexibility with EU-wide remote work plus office options in Stuttgart and Berlin
- Permanent contract for all successful applicants regardless of location
- 5+ years of Python experience with ~10 years overall software engineering or data experience
- Hands-on experience with large language models and vector databases required
- Experience building AI agents with frameworks like LangGraph, LangChain, or CrewAI
Role overview
At Makersite, we're pioneering the future of sustainable product development and digital collaboration. As a leading platform for product lifecycle management (PLM), we empower companies to make smarter, more sustainable decisions across their entire supply chain. Our cutting-edge software enables teams to design, prototype, and manufacture with transparency, efficiency, and responsibility—reducing environmental impact while optimizing performance. We're a fast-growing, innovative company that thrives on creativity, collaboration, and continuous learning. This Data Scientist (m/f/x) role focuses on developing and deploying production-grade AI systems using advanced architectures like RAG and AI agents, with strong emphasis on scalability, reliability, and cross-functional collaboration during a high-growth phase.
Responsibilities
- Build, deploy, and maintain scalable APIs that serve AI/ML models in production environments
- Own end-to-end delivery of AI solutions, from prototyping to fully productionized systems
- Design and implement Retrieval-Augmented Generation (RAG) systems using vector databases
- Build and orchestrate AI agents using frameworks such as LangGraph, CrewAI, or similar
- Evaluate and select appropriate large language models (LLMs) and foundation models based on specific use cases
- Continuously optimize model inference for latency, cost efficiency, and throughput at scale
- Identify bottlenecks and implement improvements to ensure high-performing systems
- Implement robust monitoring, logging, and alerting for deployed models and services
- Ensure system reliability, uptime, and performance through best practices in production ML systems
- Build and maintain CI/CD pipelines for seamless testing, deployment, and iteration of AI systems
- Contribute to evolving engineering standards as the company transitions from rapid experimentation to more structured, scalable operations
- Work closely with product and engineering teams to integrate AI capabilities into core products
- Translate business problems into technical solutions and clearly communicate trade-offs
- Help bring stability and structure to AI development processes during a high-growth, scale-up phase
- Balance speed of execution with the need for maintainable, well-documented, and scalable systems
- Take ownership of ambiguous problems and drive them through to practical, production-ready outcomes
Requirements
- 5+ years of experience in Python, with ~10 years of overall software engineering or data experience (candidates transitioning from backend engineering are welcome)
- Proven experience building and deploying production-grade APIs (preferably with FastAPI; REST/GraphQL experience is a plus)
- Hands-on experience working with large language models (LLMs) and LLMOps, including prompt engineering, fine-tuning, and evaluation (e.g., GPT, Claude)
- Strong experience fine-tuning open-source models (e.g., Hugging Face ecosystem)
- Practical experience designing and working with vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector)
- Experience building AI agents using frameworks such as LangGraph, LangChain, CrewAI, or similar
- Solid understanding of model deployment and serving (e.g., vLLM, TGI, or managed endpoints)
- Experience with CI/CD pipelines and modern deployment practices (Docker, Kubernetes, GitHub Actions)
- Strong experience working with and processing large-scale text datasets
- Residing in and legally permitted to work in the EU
Nice to have
- Experience with MLOps platforms such as MLflow or Weights & Biases
- Familiarity with cloud AI ecosystems (e.g., AWS Bedrock, GCP Vertex AI, Azure OpenAI)
- Contributions to open-source AI/ML projects
- Experience in the sustainability or climate/product domain
- Background in B2B SaaS environments
- Prior experience in a startup or scale-up environment (approximately 100–300 employees)
Benefits
- Competitive Salary
- 30 Days Paid Time Off
- Remote-First Flexibility – Work from anywhere in the EU, with the option to collaborate in person at our offices in Stuttgart, Berlin (role dependent)
- Generous Learning & Development Budget
- Choose Your Ideal Work Equipment – Whether you prefer Apple or Microsoft, we'll equip you with the tools you need to excel
Additional details
- This role is a fixed, permanent position
- All successful applicants will receive a permanent employment contract regardless of location
- Builder mindset: Comfortable owning systems end-to-end, from experimentation through to production
- Bias for action: Operates effectively in a fast-paced, evolving environment with shifting priorities
- Systems thinker: Designs solutions with scalability, reliability, and maintainability in mind
- Pragmatic decision-making: Balances technical excellence with speed and business impact
- Ownership & accountability: Takes responsibility for outcomes, not just outputs
- Clear communicator: Able to articulate complex technical concepts to both technical and non-technical stakeholders
- Makersite is an equal opportunity employer
- Company culture values inclusivity and fosters a culture of collaboration and mutual respect
- Remote-first company with trust-based work arrangement