MLOps Engineer

MLOps Engineer

Full-Time 43200 - 72000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build and manage infrastructure for cutting-edge AI models, ensuring efficiency and scalability.
  • Company: Ultralytics is a leading innovator in AI, focused on developing world-class YOLO models.
  • Benefits: Enjoy hybrid flexibility, generous time off, and the latest tech gear.
  • Why this job: Join a high-energy team dedicated to shaping the future of Vision AI with audacious goals.
  • Qualifications: 5+ years in DevOps or MLOps, strong Python skills, and experience with cloud platforms.
  • Other info: This role demands exceptional dedication and a commitment to excellence in a fast-paced environment.

The predicted salary is between 43200 - 72000 £ per year.

Who We Are 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. Your work will be critical to ensuring that our state-of-the-art models are accessible, reliable, and performant for our global user base. ️ 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 Competitive Salary: Highly competitive based on experience. Startup Equity: Participate directly in our company\’s growth and success. Hybrid Flexibility: 3 days per week in our brand-new office – 2 days remote. Generous Time Off: 24 days vacation, your birthday off, plus local holidays. Flexible Hours: Tailor your working hours to suit your productivity. Tech: Engage with cutting-edge AI projects. Gear: Brand-new Apple MacBook and Apple Display provided. Team: Become part of a supportive and passionate team environment. If you are driven to build the backbone of next-generation AI and are ready for an intense and rewarding challenge, we encourage you to apply to Ultralytics.

MLOps Engineer employer: Ultralytics

At Ultralytics, we pride ourselves on being an exceptional employer, offering a dynamic and high-energy work environment in our brand-new London office. Our culture is built on innovation and excellence, providing employees with generous benefits such as competitive salaries, hybrid working options, and ample time off, all while fostering personal and professional growth through challenging projects in cutting-edge AI. Join us to be part of a passionate team dedicated to making a global impact in the world of Vision AI.
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Contact Detail:

Ultralytics Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land MLOps Engineer

Tip Number 1

Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Docker, Kubernetes, and CI/CD pipelines. Having hands-on experience or projects showcasing these skills can set you apart during discussions.

Tip Number 2

Network with current or former employees of Ultralytics on platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during your interview.

Tip Number 3

Prepare to discuss real-world scenarios where you've optimised machine learning models or built MLOps infrastructure. Being able to articulate your problem-solving process and the impact of your work will demonstrate your fit for the high-performance environment at Ultralytics.

Tip Number 4

Showcase your passion for AI and innovation by staying updated on the latest trends and advancements in the field. Mentioning recent developments or projects that excite you during your interview can highlight your enthusiasm and commitment to the industry.

We think you need these skills to ace MLOps Engineer

Python Programming
Machine Learning Frameworks (e.g., PyTorch)
CI/CD Pipeline Development
Containerization (Docker)
Kubernetes Orchestration
Cloud Platforms (GCP, AWS, Azure)
Infrastructure as Code (IaC) Tools (e.g., Terraform, Ansible)
GPU Acceleration (CUDA)
Model Optimization for Inference
MLOps Tools (e.g., MLflow, Kubeflow, Weights & Biases)
Problem-Solving Skills
Experience in Fast-Paced Environments
Collaboration with AI Research Teams
Experiment Tracking and Versioning

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in MLOps, DevOps, or SRE roles. Emphasise your proficiency in Python, CI/CD pipelines, and cloud platforms like GCP or AWS, as these are crucial for the role.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of Ultralytics' mission. Mention specific projects or experiences that demonstrate your ability to thrive in a high-performance environment.

Showcase Relevant Skills: In your application, clearly outline your experience with containerization (Docker), orchestration (Kubernetes), and any MLOps tools you've used. This will help you stand out as a candidate who meets their technical requirements.

Highlight Cultural Fit: Ultralytics values intensity and dedication. In your application, convey your commitment to excellence and your readiness to contribute to a fast-paced, high-energy environment. Share examples of how you've thrived under pressure in previous roles.

How to prepare for a job interview at Ultralytics

Showcase Your Technical Skills

Be prepared to discuss your experience with Python, CI/CD pipelines, and cloud platforms like GCP or AWS. Bring examples of past projects where you successfully implemented MLOps practices.

Demonstrate Problem-Solving Abilities

Expect technical questions that assess your problem-solving skills in high-pressure situations. Think of scenarios where you've had to troubleshoot issues in machine learning systems and be ready to explain your thought process.

Understand the Company Culture

Ultralytics values intensity and dedication. Be ready to discuss how you thrive in fast-paced environments and your commitment to achieving extraordinary results. Share examples of how you've taken ownership in previous roles.

Prepare for Collaboration Questions

Since the role involves working closely with AI researchers, prepare to discuss your experience in collaborative settings. Highlight instances where you've successfully transitioned models from research to production and how you managed communication within teams.

MLOps Engineer
Ultralytics
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  • MLOps Engineer

    Full-Time
    43200 - 72000 £ / year (est.)

    Application deadline: 2027-06-16

  • U

    Ultralytics

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