DevOps Engineer

About the team

Adaptive ML is building a reinforcement learning platform to tune, evaluate, and serve  specialized language models. We are pioneering the development of task-specific LLMs using synthetic data, creating the foundational tools and products needed for models to self-critique and self-improve based on simple guidelines. Adaptive Engine enables companies to build and deploy the best LLMs for their business. Our founders previously worked together to create state-of-the-art open LLMs. We closed a $20M seed with Index & ICONIQ in early 2024 and are live with our first enterprise customers (e.g., AT&T).

Our Product Team is responsible for building and shipping the first frontier-grade, end-to-end LLM alignment platform. Product Staff Engineers collaborate closely with (1) the Technical Staff to integrate our latest scientific breakthroughs into the product, and (2) the Commercial Staff to learn from customer needs and rapidly iterate based on real-world feedback.

About the role

As a DevOps Engineer on our Product Team, you will help design, package, and operate our technology, turning it into an exceptional product for both SaaS consumption and on-premise deployment. You’ll play a foundational role in shaping the infrastructure behind how we build, test, deploy, and run our systems. This includes everything from GPU orchestration and CI/CD pipelines to observability, security, and deployment automation. As we scale our product and customer footprint, you’ll help ensure our systems are fast, reliable, and easy to operate—whether running in the cloud or in tightly controlled environments.

You’ll work cross-functionally with product, engineering, and research to turn evolving requirements into stable, repeatable, and production-ready infrastructure. This role is ideal for someone who thrives at the intersection of software engineering, infrastructure, and operations—and who enjoys building robust systems that power real-world ML products. We’re looking for self-driven, business-minded individuals who are excited by the challenge of making a highly technical product more reliable, accessible, and responsive. As an early member of the Product Team, you’ll also help shape how the team itself grows.

This role is ideally in-person at our Paris or New York office, but we are also open to a hybrid of remote with regular visits to one of our offices.

Your responsibilities

• Design and manage scalable infrastructure to support ML training, inference, and data pipelines;

• Maintain & optimize customer-facing artifacts, such as our Helm Chart, our Docker Compose template and our private Docker registry;

• Expand & operate our SaaS offerings (multi-tenant and single-tenant), including maintaining Terraform pipelines, networking configuration (e.g., WAF, DNS) & computing pools at hyperscalers, and neoclouds (i.e., both bare metal VMs & Kubernetes clusters);

• Develop observability tooling—monitoring, alerting, logging—for core infrastructure and services;

• Assist with audit & implementation of continuous security practices, including code & image scanning, log storage, data retention & encryption policies, security notification & alerting.

Your (ideal) background

The background below is only suggestive of a few pointers we believe could be relevant. We welcome applications from candidates with diverse backgrounds; do not hesitate to get in touch if you think you could be a great fit, even if the below doesn't fully describe you.

• Proven experience with infrastructure-as-code (IaC), particularly Terraform and CloudFormation, for managing scalable and reproducible environments across internal and external deployments;

• 2+ years of experience managing containerized environments, with expertise in container security, networking, and orchestration (Kubernetes preferred);

• Backend programming skills (e.g., Rust, Python, Typescript and/or Node);

• Track record of operating & securing B2B SaaS systems;

• B2B SaaS DevOps experience in a regulated environment a strong plus (SOC2, HIPAA, etc);

• M.Sc. /Ph.D. in computer science, or demonstrated experience in software engineering;

• Passionate about the future of generative AI, and eager to build foundational technology for training specialized models with reinforcement learning.

Benefits

• Comprehensive medical (health, dental, and vision) insurance;

• 401(k) plan with 4% matching (or equivalent);

• Unlimited PTO — we strongly encourage at least 5 weeks each year;

• Mental health, wellness, and personal development stipends;

• Visa sponsorship if you wish to relocate to New York or Paris.