At a Glance
- Tasks: Design and maintain infrastructure for advanced AI systems, from research to production.
- Company: Leading AI organisation specialising in Defence and Security technologies.
- Benefits: Competitive salary up to £95k, bonus, and opportunities for travel.
- Other info: Dynamic role with potential for career growth in a high-tech environment.
- Why this job: Join a team of experts and work on cutting-edge AI applications.
- Qualifications: Strong experience in MLOps, Python, and ML infrastructure required.
The predicted salary is between 63000 - 77000 £ per year.
Must hold active clearance – SC or MoD DV
Up to £95k DoE plus bonus
4 days on site in Brentford – future expensed travel to client site in Cambridge
Strong experience across MLOps, ML infrastructure and production AI systems
We are recruiting a Senior AI/ML Engineer with strong MLOps and ML infrastructure experience for a highly technical AI organisation delivering advanced computer vision and machine learning technologies across Defence, Security and other high-performance environments.
You’ll work alongside AI researchers, software engineers and technical leadership to take cutting‑edge machine learning research from R&D through to reliable, production‑ready systems. The role offers the opportunity to work on challenging AI applications deployed across both large‑scale cloud environments and edge platforms.
What will the Senior MLOps Engineer be doing?
You will design, build and maintain the infrastructure that powers advanced AI systems from research through to production. You’ll develop distributed training pipelines, build ML lifecycle infrastructure, optimise models for deployment and support reliable AI systems across cloud and edge environments.
Key Skills and Requirements
- Strong Python/PyTorch and ML infrastructure experience
- Experience with distributed ML training using Ray, DeepSpeed or PyTorch Lightning
- Strong MLflow, model registry and ML lifecycle experience
- Experience with TensorRT, ONNX, quantisation and model deployment
- Strong Docker, CI/CD and GitHub Actions experience
- Experience with Prometheus/Grafana monitoring and production observability
- Cloud/edge AI deployment, with NVIDIA Jetson/DeepStream highly desirable
- Knowledge of Kubernetes, Kubeflow, Metaflow and Kafka advantageous
- Computer vision, aerial/satellite/ISR experience highly beneficial
Senior MLOps Engineer in Brentford employer: Searchability®
Join a dynamic and innovative technology company in the heart of Manchester, where you'll have the opportunity to lead technical innovation on a mature SaaS platform. With a strong emphasis on collaboration, employee development, and a transparent progression framework, this role offers not only competitive pay but also unique benefits like profit sharing and regular team-building activities. Experience a vibrant work culture that prioritises autonomy and continuous improvement, making it an excellent place for passionate engineers to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps Engineer in Brentford
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We think you need these skills to ace Senior MLOps Engineer in Brentford
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Searchability®. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Searchability®
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
