Role Overview

Join Datadog's innovative Senior Software Engineer (MLOps) – Training & Registry team in Paris or Sophia Antipolis, France. We're building a next-generation AI platform that powers seamless training, tracking, and deployment of ML and LLM models at scale. This high-impact role focuses on foundational infrastructure for AI development, including distributed systems for job orchestration, model lifecycle management, and training observability.

As a key player in Datadog's AI evolution, you'll design robust backend systems that enable applied scientists to iterate rapidly and reliably. Powering everything from classic ML workflows to large-scale LLM fine-tuning, this position offers exposure to cutting-edge technologies and collaboration with platform teams, scientists, and infrastructure stakeholders. Datadog's hybrid workplace model supports work-life harmony while fostering creativity through office culture.

Key Responsibilities at Datadog

• Design and implement scalable systems for training orchestration, artifact tracking, and model registration across multi-data centers and cloud regions.
• Streamline ML experimentation workflows integrating Ray, Airflow, and interactive notebooks for rapid iteration.
• Develop APIs and services that let scientists launch, debug, and track training jobs effortlessly.
• Build version control and metadata systems ensuring reproducibility and traceability of model artifacts.
• Collaborate with AI infra teams (LLMObs, Compute) for consistent experiences and integrated Datadog telemetry.
• Mentor engineers, drive architectural decisions, and establish technical standards.
• Optimize infrastructure for LLM fine-tuning and embedding generation at enterprise scale.
• Implement observability solutions leveraging Datadog's monitoring platform for training jobs.
• Enhance platform reliability across distributed systems in cloud-native environments.

Qualifications & Requirements

To succeed as a Senior MLOps Engineer at Datadog, you'll bring:

• 6+ years in backend, distributed systems, or platform engineering.
• Hands-on experience with ML platforms supporting training or model lifecycle workflows.
• Proficiency in API design, large-scale data management, and reliable/observable systems architecture.
• Fluency in Python or Go, plus cloud-native expertise (Kubernetes, object stores, queues).
• Skill in cross-functional collaboration, translating science needs into engineering solutions.
• Bonus: Model registries, MLflow/Weights & Biases, distributed training frameworks.

Datadog welcomes passionate technologists—even if you don't meet every qualification, apply to grow with us!

Salary & Benefits

Earn competitive compensation in Paris/Sophia Antipolis MLOps market: €85,000 - €120,000 yearly base, plus equity. Enjoy:

• New hire RSUs and ESPP for ownership.
• Global health & mental health benefits for family (age 6+).
• Professional development, training, career pathing.
• Mentor/buddy programs and Community Guilds.
• Inclusion Talks and inclusive culture.
• Commuter & fitness reimbursements.
• Hybrid work with office perks. (Varies by location.)

Why Join Datadog?

Datadog (NASDAQ: DDOG) is the leading cloud monitoring and security platform, delivering growth and profitability. Break down silos in the cloud age with infrastructure monitoring for entire tech stacks. Built by engineers for engineers, we serve all industries. Champion professional development, diversity, innovation, and work excellence. Join our collaborative, people-first community solving tough problems in AI, observability, and DevOps. Experience #DatadogLife!

Work on foundational AI infrastructure powering Datadog's evolution. Gain expertise in MLOps, distributed training, and observability while advancing your career in France's tech hubs.

How to Apply

Ready to shape AI infrastructure at Datadog? Apply now for Senior Software Engineer (MLOps) in Paris or Sophia Antipolis! Submit your resume highlighting MLOps, Python/Go, and distributed systems experience. Join thousands building the future of cloud observability. Don't miss this high-impact opportunity—positions fill fast!