ML Platform Engineer

About us

Bleu Robotics is an AI company developing universal AI software for the deployment of advanced robots , humanoids, mobile manipulators, and industrial arms, in real factories. The convergence of humanoid robotics and modern AI is one of the most significant technical opportunities of the decade, and most of the work today still happens in research settings. We are building the software layer required to bring it into operational use.

We have a strong ambition to become the next Microsoft to run on every industrial humanoid. We have closed our pre-seed round with Top-tier fund to deploy our robot in Tier 1 manufacturing facilities.

We are looking for deeply passionate scientists who can help us push the frontier and build a major lab in physical AI.

Our vision

To enable a robot to learn a new industrial task from a few demonstrations and operate autonomously, with under one hour between the start of the demonstration and the start of deployment.

This objective shapes our roadmap and every technical decision we make.

THE ROLE

We are hiring an ML Platform Engineer to put our robot learning stack in the cloud and own the full stack. The platform will let customers run our learning pipelines on their own data as a hosted service; its exact scope will evolve with the product.

You will be the first engineer at Bleu Robotics with cloud expertise. The scope covers infrastructure, training and inference services, the web front end, security, and cost. The choice of cloud provider and web framework is open; you will make it with the team.

The role is based in Paris and is on-site.

BACKGROUND

We are equally interested in two kinds of background:

1. software or ML platform engineer who has built and operated a cloud service that runs training or inference jobs on data uploaded by users (e.g., an ML platform team, an MLOps product, a SaaS that runs compute on customer data).

2. backend or full-stack engineer with solid DevOps experience who has shipped a web product on a major cloud provider and wants to work on robot learning.

Experience with robotics or robot learning is appreciated but not required. You will learn the learning stack from the team; the team will learn cloud practices from you.

RESPONSIBILITIES

• Design the architecture of the platform and select the cloud provider, orchestration layer, and web stack, in agreement with the team

• Package our training and inference pipelines (Python, PyTorch) as cloud services: job scheduling, GPU provisioning, artifact storage, versioning of datasets and policies

• Build the web application through which users upload data, follow training runs, and download policies, including its front end and API

• Add interactive, browser-based components to the platform, including simulation, as the product evolves

• Set up infrastructure as code, CI/CD, monitoring, logging, and alerting for the platform

• Implement authentication, per-customer isolation, and data protection for confidential industrial data

• Control cloud costs: GPU usage, storage, and idle resources

• Bring cloud and DevOps practices to the rest of the engineering team through documentation, reviews, and training

REQUIRED QUALIFICATIONS

• Master's degree or PhD in computer science or a related field, followed by 2 to 3 years of professional experience building and operating a comparable cloud service

• Hands-on experience running production workloads on at least one major cloud provider (AWS, GCP, Azure, or a European provider such as Scaleway or OVHcloud)

• Proficiency with containers and orchestration (Docker and Kubernetes or a managed equivalent) and with infrastructure as code (Terraform or similar)

• Strong Python development skills for backend services, including asynchronous job execution

• Front-end development experience with a modern web framework (React, Vue, Svelte, or similar), sufficient to ship the user-facing application yourself

• Experience with CI/CD, monitoring, and security practices for a multi-tenant service

• Comfortable working in Linux environments with Git

• Professional proficiency in English, the official language of the team. Proficiency in French is not required; many of our employees do not speak French.

PREFERRED QUALIFICATIONS

The strongest candidates will combine cloud fluency with experience across several of the following:

• ML infrastructure: training job orchestration, GPU scheduling, experiment tracking, model registries

• PyTorch and the Python machine learning ecosystem