ML Platform Devops Engineer Snr

ML Platform DevOps Engineer Sr

Paris, 75, FR

Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients. We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

ML Platform Team

The ML Platform team is focused on enhancing researcher productivity in training machine learning (ML) models by developing libraries, services, and best practices, and ensuring robust ML production at scale. The aim is to provide a seamless path from experimentation to production that integrates with existing systems and boosts efficiency for model deployment. The team mandate consists of addressing pain points, advancing organizational ML capabilities, and leveraging platform engineering with a modular, self-service approach. It balances immediate user needs with sustainable technical decisions, emphasizing best practices and automation. The team is composed of profiles working on cross-functional projects as well as engineers supporting functional teams in their ML journey.

Your Role

As a Senior DevOps Engineer in the ML Platform team, you'll leverage your strong software engineering background, proficiency in Python, and hands-on experience with AWS. Your role is to collaborate with developers and engineers to ensure software development adheres to established processes and functions effectively. You will also partake in project planning and technical choices.

Key Responsibilities:

• Implement testing, development, automation tools, and IT infrastructures for the ML Platform team and its users.
• CI/CD tools, handling configuration management.
• Define and establish processes for testing, development, release, updates, and support in DevOps operations.
• Drive continuous improvement by building pipelines for integration, development, and deployment.
• Implement and maintain monitoring systems.
• Maintain and enhance the team's cloud infrastructure.
• Promote and implement automation processes.
• Enhance security protocols by conducting vulnerability assessments and risk management to deploy cybersecurity measures.

Your Skills

We are looking for candidates with 10+ years of experience in software development at large, and 5+ years facing production challenges in the cloud, 3 of which with AWS.

Mandatory

Technical

• Proficient in Terraform and AWS.
• Solid experience with CI/CD, ideally with GitLab CI and Jenkins.
• Extensive experience using Docker and managing large-scale Docker images within an organization.
• Skilled in setting up and maintaining monitoring systems.
• Deep familiarity with UNIX-based systems.

Work methodology

• Experience with Agile, emphasizing flexibility and pragmatism over strict adherence.

Soft Skills

• Ability to articulate and defend strong opinions constructively, fostering consensus.
• Experience to understand not all decisions will go your way, with the ability to disagree yet commit.
• User-centered mindset while avoiding short-term solutions.
• Skill in engaging and motivating colleagues to adopt best practices.
• Commitment to team productivity and resilience through skill-sharing, beyond individual

Nice to Have

Technical

• Experience adjacent to ML related topics
• Having worked in an on-premise environment, Slurm appreciated

If you don't meet every requirement but believe you'd be a great fit, feel free to reach out to us.

Equal Opportunities Statement

We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success. CFM is a signatory of the Women Empowerment Principles.