MLOps Engineer

Ultralytics

London

Hybrid

GBP 90,000 - 140,000

Full time

14 days+

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Benefits offered by this job

Competitive salary

Startup equity

24 days vacation

Flexible hours

Brand-new Apple MacBook

Supportive team environment

Job summary

A leading AI technology firm in London seeks an MLOps Engineer to build and manage the infrastructure for cutting-edge AI models. Candidates should possess over 5 years of DevOps experience and strong skills in Python and ML frameworks. This role offers competitive compensation with hybrid work flexibility and generous time off, in a dynamic, high-performance environment.

Qualifications

5+ years of experience in a DevOps, SRE, or MLOps role.
Proven experience building and managing CI/CD pipelines for machine learning systems.
Strong proficiency in Python and extensive experience with ML frameworks like PyTorch.
Proven experience building and managing CI/CD pipelines for ML systems.
Deep expertise with Docker and Kubernetes.
Hands-on experience with cloud providers (GCP/AWS/Azure).
Experience with IaC tools such as Terraform or Ansible.
Familiarity with CUDA and model optimization for inference.
Knowledge of MLOps tools for experiment tracking and model serving (MLflow, Kubeflow, Weights & Biases).
Excellent problem-solving in fast-paced environments.

Responsibilities

Designing, building, and maintaining MLOps infrastructure on cloud platforms.
Developing and managing automated CI/CD pipelines for model training and deployment.
Containerizing applications and models using Docker and orchestrating with Kubernetes.
Optimizing YOLO models for diverse deployment targets including GPUs and edge devices.
Implementing robust systems for model monitoring and data drift detection.
Collaborating with AI research to productionize models within the Ultralytics HUB ecosystem.
Managing experiment tracking and versioning with MLflow and DVC.

Skills

Python

CI/CD pipelines

Docker

Kubernetes

GCP

Ansible

ML frameworks

Problem-solving skills

MLflow

Kubeflow

Weights & Biases

Tools

MLflow

Terraform

Ansible

MLflow

Kubeflow

Weights & Biases

TensorRT

OpenVINO

Job description

Overview

At Ultralytics, we relentlessly drive innovation in AI, building the world's leading YOLO models. We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI.

Location and Legalities

This full-time MLOps Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.

What You\'ll Do

As an MLOps Engineer at Ultralytics, you will build and manage the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include:

Designing, building, and maintaining our MLOps infrastructure on cloud platforms like GCP and AWS.
Developing and managing automated CI/CD pipelines for model training, validation, and deployment using tools like GitHub Actions.
Containerizing our applications and models using Docker and orchestrating them with Kubernetes for scalable model serving.
Optimizing the performance of our Ultralytics YOLO11 models for various deployment targets, from high-performance cloud GPUs with CUDA to edge devices using frameworks like TensorRT and OpenVINO.
Implementing robust systems for model monitoring and maintenance to track performance and detect data drift.
Collaborating closely with our AI research team to streamline the transition of models from research to production within the Ultralytics HUB ecosystem.
Managing our experiment tracking and versioning using tools like MLflow and DVC.

Skills and Experience

5+ years of experience in a DevOps, SRE, or MLOps role.
Strong proficiency in Python and extensive experience with ML frameworks like PyTorch.
Proven experience building and managing CI/CD pipelines for machine learning systems.
Deep expertise with containerization Docker and orchestration technologies Kubernetes.
Hands-on experience with at least one major cloud provider (GCP, Azure, AWS).
Experience with Infrastructure as Code (IaC) tools such as Terraform or Ansible.
Familiarity with GPU acceleration using CUDA and model optimization for inference.
Knowledge of MLOps tools for experiment tracking, and model serving such as MLflow, Kubeflow, or Weights & Biases.
Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity environment.

Cultural Fit - Intensity Required

Ultralytics is a high-performance environment for world-class talent obsessed with achieving extraordinary results. We operate at a relentless pace, demanding exceptional dedication and an unwavering commitment to excellence, guided by our mission, vision, and values. Our team thrives on audacious goals and absolute ownership. This is not a conventional workplace. If your priority is predictable comfort or a standard work-life balance over the relentless pursuit of progress, Ultralytics is not for you. We seek driven individuals prepared for the profound personal investment required to make a defining contribution to the future of AI.

Compensation and Benefits