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- Tasks: Build and manage AI infrastructure, optimising performance and ensuring efficient machine learning lifecycle.
- Company: Ultralytics is a leading innovator in AI, focused on developing cutting-edge YOLO models.
- Benefits: Enjoy hybrid flexibility, generous time off, and the latest tech gear like a MacBook.
- Why this job: Join a dynamic team shaping the future of Vision AI with impactful projects.
- Qualifications: 5+ years in DevOps or MLOps, strong Python skills, and experience with cloud platforms.
- Other info: This role is onsite in London; visa sponsorship is not 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 (Python) employer: Ultralytics
Contact Detail:
Ultralytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Engineer (Python)
✨Tip Number 1
Familiarise yourself with Ultralytics' YOLO models and their applications in AI. Understanding the specific technologies and innovations they are working on will help you demonstrate your passion and knowledge during any discussions.
✨Tip Number 2
Network with current or former employees of Ultralytics on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which can be invaluable when preparing for interviews.
✨Tip Number 3
Showcase your hands-on experience with CI/CD pipelines and cloud platforms in your conversations. Be ready to discuss specific projects where you've implemented these technologies, as practical examples can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss how you would optimise machine learning models for different deployment targets. Having a clear understanding of performance optimisation techniques will demonstrate your technical expertise and readiness for the role.
We think you need these skills to ace AWS Engineer (Python)
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the AWS Engineer position at Ultralytics. Familiarise yourself with their AI models and the technologies mentioned in the job description.
Tailor Your CV: Customise your CV to highlight relevant experience in DevOps, MLOps, or SRE roles. Emphasise your proficiency in Python and any hands-on experience with cloud platforms like AWS or GCP, as well as your work with CI/CD pipelines.
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 requirements, particularly in building and managing MLOps infrastructure.
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 is crucial for a technical role.
How to prepare for a job interview at Ultralytics
✨Showcase Your Python Skills
As an AWS Engineer, your proficiency in Python is crucial. Be prepared to discuss specific projects where you've used Python, especially in relation to machine learning frameworks like PyTorch. Highlight any challenges you faced and how you overcame them.
✨Demonstrate Your Cloud Experience
Ultralytics values hands-on experience with cloud platforms. Be ready to talk about your experience with AWS or GCP, detailing how you've built and managed infrastructure for machine learning models. Discuss any CI/CD pipelines you've developed and the tools you used.
✨Understand MLOps Principles
Familiarise yourself with MLOps best practices, as this role focuses on the machine learning lifecycle. Be prepared to explain how you ensure efficiency and scalability in model training and deployment, and share examples of monitoring systems you've implemented.
✨Express Your Passion for AI
Ultralytics is looking for individuals who are genuinely excited about AI. During the interview, convey your enthusiasm for the field and discuss any personal projects or research you've undertaken that demonstrate your commitment to advancing AI technology.
