Infrastructure Engineer - ML Ops & Observability (Hybrid)

hcompany; Paris; Hybride; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Career development

Collaborative team

Résumé du poste

H is building a next‑generation AI infrastructure team. The role focuses on designing robust infrastructure to support model and agent development, including training pipelines, data flows, and inference services.

You will own observability, telemetry, and scalable runtimes across multi‑tenant and on‑prem deployments. The ideal candidate brings strong scripting knowledge (Python or JavaScript/TypeScript), hands‑on experience with modern monitoring stacks, and a passion for distributed cloud

Qualifications

• MUST HAVE: Observability and monitoring tools such as Datadog, Prometheus, Grafana.
• MUST HAVE: Proficiency in a modern language (Python or JavaScript/TypeScript).
• NICE TO HAVE: ML Ops or Data Engineering experience.
• NICE TO HAVE: Experience architecting and deploying distributed systems on public cloud (AWS, Azure, GCP).
• NICE TO HAVE: Containerization and orchestration tools (Docker, Kubernetes).
• NICE TO HAVE: Infrastructure as code (CDK, Terraform).
• NICE TO HAVE: CI/CD management experience (GitHub Actions, GitLab CI, TeamCity).

Responsabilités

• Designing and managing the infrastructure to support research efforts in Model and Agent development incl. training infrastructure, data pipelines and inference.
• Product Engineering efforts on H Company’s agent platform including client-facing APIs and agent runtimes within various deployment scenarios (multi-tenant and on-prem).
• Setup and maintain observability and monitoring strategies.

Connaissances

Observability and monitoring

Python/JavaScript

Distributed systems familiarity

Outils

Datadog

Prometheus

Grafana

Docker

Kubernetes

Description du poste

H is building a next‑generation AI infrastructure team. The role focuses on designing robust infrastructure to support model and agent development, including training pipelines, data flows, and inference services.

You will own observability, telemetry, and scalable runtimes across multi‑tenant and on‑prem deployments. The ideal candidate brings strong scripting knowledge (Python or JavaScript/TypeScript), hands‑on experience with modern monitoring stacks, and a passion for distributed cloud