MACHINE LEARNING & COMPUTER VISION PLATFORM ENGINEER

STATION F; Paris; Hybrid; EUR 55,000 - 73,000; Full time

Job summary

Scortex is looking for an ML Platform Engineer to join Paris-based team, bridging software engineering, MLOps, and cloud infra. You will maintain tooling, deployment pipelines and monitoring to enable researchers and engineers to move faster and deploy models reliably in production.

The role emphasizes automation, security, and documentation, with collaboration across ML researchers and product teams. Some visits to factory sites may occur; partial remote possible.

Qualifications

• Experience tooling to support ML/CV R&D.
• Experience with MLOps & orchestration tools (MLFlow, Kubeflow, DVC, Airflow).
• Experience deploying ML models to production.
• Strong Python proficiency.
• Ops and sysadmin skills: networking, Linux, virtualization.
• CI/CD pipelines knowledge (GitHub Actions, etc.).
• Configuration management (Ansible, etc.).
• Monitoring systems (Prometheus, Grafana).
• Public cloud experience (Azure).
• Databases and messaging (PostgreSQL, Kafka).

Responsibilities

• Build internal tooling to support data preparation, experiment tracking, model training, and evaluation.
• Design and maintain model deployment pipelines for production inference systems.
• Support deployment and monitoring of computer vision models in production environments.
• Improve & Automate Provisioning and Scaling of physical and virtual infrastructure (incl. containers, software versions and configurations, databases, cloud resources, networking, user accounts, etc.).
• Improve & Automate Monitoring of our systems with dashboards, collectors and integrations.
• Optimizations (of Billed Cost, Dev Time or Latency/Throughput), ranging from database indexes and configurations to appropriate device selection.

Skills

ML tooling

MLFlow

Kubeflow

DVC

Airflow

Python

Networking

Linux

CI/CD

Ansible

Prometheus

Grafana

Azure

PostgreSQL

Kafka

Docker

Kubernetes

Education

Master's Degree

Tools

Docker

Kubernetes

MLFlow

Kubeflow

DVC

Airflow

Job description

At Scortex, we love factories. The smell of grease, the sparks of welding, the jingling of conveyor belts. We appreciate the beauty of a well-crafted industrial process, delivering value at a massive scale in the physical world.

That is why it pains us to see manufacturing companies struggle with their quality. Throwing away parts by the thousands, or missing the needle in the haystack, letting faulty products slip through their tired eyes, despite all their efforts. We decided to solve this major headache of theirs, by building the required technology and making it accessible to everyone.

Leveraging Machine Learning, Our Platform Allows Customers To

• detect faulty parts on a production line, automatically, in real-time,
• know and understand quality issues at a large scale,
• dynamically improve the quality of the production.

Scortex is a team of passionate individuals, in a unique blend of the tech and manufacturing worlds.

Job Description

As a ML Platform Engineer, you will work at the intersection of software engineering, machine learning operations, and cloud infrastructure. You will maintain and evolve cloud infrastructure, tools, pipelines, and deployment workflows that enable machine learning researchers and engineers to move faster and deploy models reliably into production.

It is expected that you place the utmost importance in automation, monitoring, security, and documentation. In addition, you will collaborate closely with ML researchers, software engineers, and product teams to improve reproducibility, scalability, and operational reliability across the ML lifecycle.

As Such, Your Tasks Will Include

• Build internal tooling to support data preparation, experiment tracking, model training, and evaluation
• Design and maintain model deployment pipelines for production inference systems
• Support deployment and monitoring of computer vision models in production environments
• Improve & Automate the Provisioning and Scaling of physical and virtual infrastructure (incl. containers, software versions and configurations, databases, cloud resources, networking, user accounts, etc.)
• Improve & Automate the Monitoring of our systems with dashboards, collectors and integrations
• Optimizations (of Billed Cost, Dev Time or Latency/Throughput), ranging from database indexes and configurations to appropriate device selection

You may occasionally visit factory sites, mainly but not limited to France and Europe.

Preferred Experience

We are looking for candidates with a minimum of 4 years of technical experience.

Preferred Experience

• Experience building tooling to support Machine Learning or Computer Vision research & development
• Experience working with MLOps & orchestration tools such as MLFLow, KubeFlow, DVC, Airflow. Additionally, experience with containerization & orchestration (Docker, Kubernetes...)
• Experience supporting machine learning workflows or deploying ML models to production
• Strong proficiency in Python
• General operations and system administration skills are appreciated: networking (debugging, virtualization, proxies, ...), Linux systems administration & virtualization (Bios/UEFI, PXE, systemd...), enterprise security tooling (OIDC, PKI...), CI/CD Pipelines (Github Actions...), configuration management (Ansible...), monitoring (Prometheus, Grafana...), public cloud (Azure...), databases (PostgreSQL, Kafka...)

Expected Soft Skills

• Languages: English at or above B2 level
• Interested in helping & supporting less technically skilled peers

Recruitment Process

3 Round Interviews

• Introduction call (30 minutes over phone)
• Technical interview (2 hours: coding exercise + technical discussion)
• Culture fit interview (1 hour)

Additional Information

• Contract Type: Full-Time
• Start Date: 01 June 2026
• Location: Paris
• Education Level: Master's Degree
• Experience: > 2 years
• Possible partial remote
• Salary: between 55000€ and 73000€ / year