At a Glance
- Tasks: Build and scale AI infrastructure for cutting-edge robotics projects.
- Company: Join a pioneering robotics company at the forefront of intelligent systems.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Fast-paced environment with exciting challenges and career advancement.
- Why this job: Make a real impact on AI systems that power physical robots.
- Qualifications: Strong Python skills and experience with ML pipelines in production.
The predicted salary is between 50000 - 70000 € per year.
We’re working with a cutting-edge robotics company building intelligent systems capable of learning real-world physical tasks. They’re now hiring an AI / ML Infrastructure Engineer to own the end-to-end infrastructure that powers model training, data pipelines, and deployment into real-world robotic systems. This is a highly technical role sitting at the intersection of machine learning, distributed systems, and robotics - not a generic MLOps position.
Key Responsibilities:
- Build and scale GPU-based training infrastructure for large ML workloads
- Develop robust data pipelines for multi-modal datasets
- Own experiment tracking, model versioning, and reproducibility
- Design and optimise model deployment pipelines (including edge inference)
- Improve CI/CD workflows for ML systems and automate infrastructure
Key Requirements:
- Strong Python and experience with PyTorch-based training pipelines
- Experience with distributed training (DDP, FSDP, DeepSpeed)
- Solid cloud experience (GCP / AWS / Azure)
- Hands-on with Docker and infrastructure-as-code (Terraform)
- Experience building ML pipelines in production environments
Desirable:
- Robotics, autonomous systems, or embodied AI experience
- GPU orchestration (Kubeflow, Kubernetes, SkyPilot)
- Edge deployment (ONNX, TensorRT)
Why Apply?
- Work on real-world AI systems deployed into physical robots
- Direct impact on cutting-edge robotics capability
- Fast-moving, high-calibre engineering environment
AI / ML Infrastructure Engineer in Bristol employer: OpenSourced Ltd
Join a pioneering robotics company in Bristol, where innovation meets real-world application. As an AI / ML Infrastructure Engineer, you'll thrive in a fast-paced, collaborative environment that values technical excellence and offers ample opportunities for professional growth. With a focus on cutting-edge technology and a commitment to employee development, this role provides a unique chance to make a tangible impact in the field of robotics.
StudySmarter Expert Advice🤫
We think this is how you could land AI / ML Infrastructure Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to folks in the robotics and AI community on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, PyTorch, or any cool ML pipelines you've built. We want to see your hands-on experience, so make it pop!
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of distributed systems and cloud platforms. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI / ML Infrastructure Engineer in Bristol
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, PyTorch, and any cloud platforms you've worked with. We want to see how your skills align with the AI/ML infrastructure role, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about robotics and AI. Share specific examples of your work with ML pipelines or distributed systems that demonstrate your fit for this role.
Showcase Your Technical Skills:In your application, be sure to mention any hands-on experience you have with Docker, Terraform, or GPU orchestration tools. We love seeing candidates who can hit the ground running, so highlight those technical chops!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at OpenSourced Ltd
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and PyTorch, as these are crucial for the role. Brush up on distributed training techniques like DDP and FSDP, and be ready to discuss how you've implemented them in past projects.
✨Showcase Your Cloud Experience
Be prepared to talk about your hands-on experience with cloud platforms like GCP, AWS, or Azure. Have examples ready that demonstrate how you've built and scaled infrastructure for ML workloads in production environments.
✨Demonstrate Your Problem-Solving Skills
Think of specific challenges you've faced in building data pipelines or optimising CI/CD workflows. Be ready to explain your thought process and the solutions you implemented, especially in relation to robotics or AI systems.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects and future directions in robotics and AI. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
