Machine Learning Engineer developing and deploying AI systems for Personio's HR platform. Collaborating with teams to integrate ML features and products ensuring data privacy and security.
About the role
- Software Engineer delivering MLOps solutions for Generative AI at DataGalaxy. Focusing on reliability and collaboration with product engineering teams in a hybrid environment.
Responsibilities
- Join the AI-Share team to help build and operate the foundations that power our Generative AI features (LLM, RAG, agents) inside the DataGalaxy data governance platform.
- This role focuses on MLOps / ModelOps delivery: making GenAI capabilities reliable in production (deployment, monitoring, cost control, traceability), while collaborating with product engineering teams across a polyglot stack.
- Contribute to the evolution of our **ModelOps platform** for GenAI: provider integrations, configuration, deployment automation, and operational tooling.
- Help implement practical patterns for running GenAI workloads in production: **evaluation**, **versioning**, **reproducibility**, safe rollouts/rollbacks, and environment management.
- Build and improve **CI/CD workflows** adapted to AI: packaging, automated checks, evaluation steps (when applicable), deployment, and rollback.
- Improve **traceability** of AI assets (configs, prompts/templates when applicable, evaluation outputs, versions) to support governance and debugging.
- Add and maintain **observability** for GenAI workloads: latency, availability, usage/cost signals, and quality-related indicators (dashboards/alerts).
- Develop and improve **GenAI features** within the platform (agent, RAG pipelines, MCP server): new capabilities, prompt engineering, bug fixes, and client-facing improvements.
- Work closely with Product / Data / Engineering to integrate GenAI capabilities into the platform in a maintainable way.
- Participate in code reviews, documentation, and post-incident follow-ups (RCA / action items), with guidance from the team.
Requirements
- Professional experience delivering production software in **Python** (services, tooling, automation): comfortable reasoning about service design, maintainability, and code quality.
- Familiarity with **CI/CD** and shipping changes to production (pipelines, environments, rollbacks, release hygiene).
- Comfortable with cloud/production constraints: reading logs/metrics, debugging issues, improving reliability over time.
- Interest in **MLOps / GenAI operations** (deploying providers/models, evaluating changes, managing latency/cost trade-offs).
- Comfortable working in a **polyglot environment**: you can read/understand code and interfaces beyond Python, and you have experience with **at least one other language** (e.g., C#, TypeScript, Java/Kotlin, Go).
- **Nice-to-have (big plus)**
- Comfortable working with **AI-assisted development tools** (e.g. coding agents, copilots) as part of your daily workflow, and open to evolving your practices as these tools mature.
- Hands-on exposure to **LLM/RAG/agents** in real projects (prompt/version management, evaluation approaches, basic safety/guardrails).
- Familiarity with managed GenAI platforms (Azure AI Foundry / Bedrock / Vertex) or similar services.
- Exposure to self-hosted inference servers (e.g. vLLM) and/or multi-model routing solutions (e.g. LiteLLM) and understanding architecture trade-offs with managed providers and for potential on-premises deployments.
- Experience with containers and orchestration (Docker, Kubernetes), plus service-to-service patterns.
- Infrastructure-as-code experience (Terraform or equivalent).
- Observability experience (OpenTelemetry, dashboards/alerting) and cost monitoring.
- Familiarity with Python API frameworks (e.g. FastAPI) and software design principles (SOLID, modular architecture, dependency injection).
- Prior exposure to parts of our broader stack (e.g., **.NET**, **Angular**) is welcome but not required.
Benefits
- Offices in the heart of Lyon (Part Dieu) and Paris (2ème arr.)
- Flexible working hours ("forfait jour")
- Remote work at will & 2.70€ net per day worked from home
- 2 weeks of working from anywhere 🌍
- Health insurance Apicil covering you and your family
- Meal vouchers (Swile card of 9€/day)
- Public transport 50% reimbursement, 100% reimbursement for your bike subscription
- Holiday Bonus 🏝️
- Quarterly team events and seminars
- An attractive remuneration according to your performance and your potential
- A real opportunity to join a French start-up that is a pioneer in its market 🚀
Job title
Job type
Experience level
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Degree requirement
Tech skills
Location requirements
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