Ingénieur Logiciel Senior (Infrastructure IA)

About the Role

What if your engineering skills could directly shape the platforms and systems behind the AI revolution? We're hiring Senior Software Engineers in Paris and across France to design, build, and scale the infrastructure that powers AI products used by millions worldwide. High-impact, technically challenging work — the kind that keeps strong engineers engaged. You'll tackle real architectural problems, write code that matters, and collaborate with sharp minds in AI research and engineering. Fully remote, flexible contract. If you're an experienced engineer who thrives on autonomy and writes clean, scalable code at the frontier of technology, we want to hear from you.

• Type: Hourly contract
• Location: Remote
• Commitment: 20–40 hours/week

What You'll Do

• Design, develop, and maintain production-grade systems supporting AI training, evaluation, and deployment pipelines.
• Write clean, well-tested, performant code in Python, TypeScript, or other modern languages.
• Build and optimize APIs, data pipelines, and backend services that run reliably at scale.
• Architect solutions balancing speed of delivery with long-term maintainability.
• Troubleshoot complex issues across distributed systems and cloud infrastructure.
• Collaborate asynchronously with cross-functional teams — ML engineers, researchers, product managers.
• Participate in code reviews and contribute to engineering best practices.
• Work independently on well-scoped projects with meaningful ownership and autonomy.

Who You Are

• 5+ years of professional software engineering experience.
• Strong proficiency in at least one modern language — Python, TypeScript/JavaScript, Go, Java, or similar.
• Solid grasp of software architecture, design patterns, and system design principles.
• Experience building and deploying backend services, APIs, or data-intensive applications.
• Comfortable with cloud platforms (AWS, GCP, or Azure) and containerized environments.
• Familiar with version control (Git), CI/CD workflows, and modern development tooling.
• Strong debugging and problem-solving — you navigate ambiguity and find root causes efficiently.
• Excellent written communication — you document decisions, explain tradeoffs, collaborate async-first.
• Self-directed and reliable — you manage your own time and deliver consistently without close supervision.

Nice to Have

• Experience with ML/AI infrastructure — training pipelines, model serving, data annotation platforms, or evaluation frameworks.
• Familiarity with large-scale data processing tools (Spark, Kafka, Airflow, or similar).
• Background in distributed systems, microservices, or event-driven design.
• Experience with infrastructure-as-code (Terraform, Pulumi) or Kubernetes.
• Contributions to open-source projects or a public portfolio of technical work.
• Previous experience in a remote-first or async-heavy engineering culture.

Why

• Work on AI infrastructure alongside top research labs and engineering teams.
• Fully remote and flexible — set your own schedule, work from anywhere.
• Tackle genuinely hard technical problems with real-world impact at scale.
• High autonomy and ownership — no micromanagement, just meaningful engineering.
• Collaborate with a global community of top-tier engineers and researchers.
• Potential for ongoing work, expanded scope, and long-term contract extension as projects grow.