Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and manage AI infrastructure, optimise models, and develop CI/CD pipelines.
- Company: Ultralytics is a leading innovator in AI, focused on Vision AI and YOLO models.
- Benefits: Enjoy hybrid work, generous time off, flexible hours, and cutting-edge tech.
- Why this job: Join a dynamic team shaping the future of AI with impactful projects.
- Qualifications: 5+ years in DevOps/MLOps, strong Python skills, and cloud experience required.
- Other info: Onsite role in London; no visa sponsorship available.
The predicted salary is between 43200 - 72000 £ per year.
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.
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.
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.
- 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.
- 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.
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.
- Hands-on experience with at least one major cloud provider (GCP, Azure, AWS).
Only those truly excited about diving headfirst into the grind, fully committed to shaping the future of AI, should apply.
Compensation and Benefits:
- Competitive Salary: Highly competitive based on experience.
- 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.
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.
Aws Engineer, DevOps, Machine Learning employer: Ultralytics
Contact Detail:
Ultralytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Aws Engineer, DevOps, Machine Learning
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as AWS, GCP, GitHub Actions, and ML frameworks like PyTorch. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the AI and MLOps community. Attend meetups, webinars, or conferences related to machine learning and DevOps. Engaging with others in the field can provide valuable insights and potentially lead to referrals for the position.
✨Tip Number 3
Prepare to discuss your previous experiences in building and managing CI/CD pipelines. Be ready to share specific examples of how you've optimised machine learning workflows, as this will demonstrate your practical knowledge and problem-solving abilities.
✨Tip Number 4
Show your passion for AI and innovation during any interviews or networking opportunities. Discuss recent advancements in AI that excite you and how you envision contributing to the future of Vision AI at Ultralytics. This enthusiasm can make a lasting impression.
We think you need these skills to ace Aws Engineer, DevOps, Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in DevOps, MLOps, and machine learning. Emphasise your proficiency in Python and any experience with CI/CD pipelines, as well as your familiarity with cloud platforms like AWS and GCP.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your eagerness to contribute to Ultralytics. Mention specific projects or experiences that align with the job description, particularly those involving model deployment and infrastructure management.
Showcase Relevant Projects: If you have worked on any relevant projects, especially those involving YOLO models or similar AI technologies, be sure to include them in your application. Highlight your role, the technologies used, and the impact of the project.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial in a high-energy environment like Ultralytics.
How to prepare for a job interview at Ultralytics
✨Show Your Passion for AI
Ultralytics is looking for individuals who are genuinely excited about AI. Be prepared to discuss your previous projects and experiences in the field, showcasing your enthusiasm and commitment to innovation.
✨Demonstrate Technical Proficiency
With a focus on MLOps, ensure you can speak confidently about your experience with Python, CI/CD pipelines, and cloud platforms like AWS or GCP. Prepare examples of how you've implemented these technologies in past roles.
✨Understand the Company’s Vision
Familiarise yourself with Ultralytics and their YOLO models. Understanding their products and how they fit into the broader AI landscape will help you articulate how you can contribute to their mission.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with the AI research team, be ready to discuss how you’ve collaborated in the past. Highlight your communication skills and ability to work in a dynamic environment.
