MLOPS ENGINEER

STATION F; Paris; Hybrid; EUR 60,000 - 90,000; Full time

Job summary

Scortex is hiring a MLOps Engineer in Paris to join a hybrid role focused on cloud infrastructure, machine learning operations, and software engineering. You will build tools, pipelines, and deployment workflows that enable researchers and engineers to move faster and deploy models reliably into production.

The role involves working with Kubernetes, on-prem and cloud resources, and strong automation culture.

Qualifications

• Minimum 2 years of technical experience.
• Experience across cloud, on-prem, or hybrid environments is a plus.
• Strong automation and scripting capabilities preferred.

Responsibilities

• Automate provisioning and scaling of physical and virtual infrastructure.
• Build and maintain deployment pipelines for ML models.
• Monitor systems with dashboards and alerts; optimize latency and costs.
• Collaborate with ML researchers and software engineers to improve reproducibility and reliability.

Skills

Networking

Linux admin

MLOps tooling

Python

CI/CD

Monitoring

Cloud platforms

Tools

MLFlow

Kubeflow

DVC

Airflow

Docker

Kubernetes

Job description

About

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.

About

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.

Job Description

As a MLOps Engineer, you will work at the intersection of cloud infrastructure, machine learning operations, and software engineering. This is an hybrid role, where you will maintain and evolve our cloud-based infrastructure while building tools, pipelines, and deployment workflows that enable machine learning researchers and engineers to move faster and deploy models reliably into production.

From web apps & microservices running in kubernetes to specialized software communicating with industrial cameras running in constrained factory environments, Scortex software requires a solid and flexible infrastructure.

It is comprised of automated code testing, integration, and deployment pipelines, compute facilities and large-scale storage systems in data centers (cloud), monitoring systems, replicated and sharded databases, on-premise analysis systems deployed in factories, and the networks (VPNs, 4G, industrial protocols etc.) to tie them all.

As a MLOps Engineer, 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

• 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
• Build internal tooling to support data preparation, experiment tracking, model training, and evaluation
• Design and maintain scalable model deployment pipelines for production inference systems
• Support deployment and monitoring of computer vision models in production environments
• Communicate with our team members, document your work and write guides to using the architecture
• Stay current, keep up to date with security and systems management tools and practices

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 2 years of technical experience.

Candidates need not meet all of these technical skills, we simply ask that the candidate has experience in at least some of them. For example, candidates that have a strong experience with system administration but only some/little cloud infrastructure or MLOps experience, but are interested to learn, should still apply !

Base Technical Skills (pick Some Of These)

• Experience with Networking Administration ( debugging, virtualization, proxies, ... )
• Experience with Linux systems Administration & Virtualization ( Bios/UEFI, PXE, systemd, ... )
• Experience working with MLOps & Orchestration tools such as MLFLow, KubeFlow, DVC, Airflow. Additionally, experience with Containerization & its orchestration ( Docker, Kubernetes, ... )
• Experience supporting machine learning workflows or deploying ML models to production
• Experience with Enterprise Security tooling ( OIDC, PKI, ... )
• Experience with CI/CD Pipelines ( Github Actions, ... )
• Experience with Configuration Management ( Ansible, ... )
• Experience with Monitoring technologies ( Prometheus, Grafana, ... )
• Experience Managing resources in the Public Cloud ( Azure, ... )
• Experience Managing and using Databases ( PostgreSQL, Kafka, ... )
• Strong proficiency in Python

Expected Soft Skills

• Languages: English at or above B2 level
• Interested in helping & supporting less technically skilled peers
• Prioritizes data-driven decisions over intuition

Recruitment Process

3 Round Interviews

• Introduction call (~25 minutes over phone)
• Technical interview (peer programming from 1 to 2hours)
• Final call (~45 minutes)

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 55€ and 73€ / year