At a Glance
- Tasks: Build and run ML infrastructure, turning research into deployable products.
- Company: Join a leading firm in the defence and security sector.
- Benefits: Competitive daily rate, flexible work schedule, and long-term contract.
- Other info: Hands-on role with excellent career growth opportunities in a dynamic environment.
- Why this job: Make a real impact by optimising ML models for production and edge deployment.
- Qualifications: Strong MLOps experience and familiarity with distributed training frameworks.
The predicted salary is between 63000 - 77000 £ per year.
Machine Learning / ML Ops Engineer
Not sure what skills you will need for this opportunity Simply read the full description below to get a complete picture of candidate requirements.
Outside IR35: £500 - 625 p/d
Active SC Clearance Required
4 days a week into East London
6 months initial contract, long term programme
The Role
We're looking for a Senior MLOps Engineer to build and run the infrastructure that takes machine learning models from research into production.
You'll work alongside AI developers, software engineers and technical leadership to turn R&D into reliable, deployable products in the cloud and on edge hardware.
The work is for a long-term programme in the defence and security sector.
This is a hands-on role, and you'll have real influence over the architecture of the ML platform.
What you'll do
- Design and maintain ML training pipelines, including distributed training at scale
- Build experiment tracking, model registry and data versioning capability
- Optimise models for production and edge deployment
- Containerise ML workloads, including multi-architecture builds for cloud and edge targets
- Implement CI/CD for ML systems
- Build monitoring and observability for models in production
- Orchestrate ML workflows and event-driven pipelines
- What you'll bring
- Strong commercial MLOps or ML engineering experience, taking models from R&D into production
- Distributed training frameworks (e. g. Ray, Deep Speed, Py Torch Lightning)
- Experiment tracking and model registries (e. g. MLflow or similar)
- Model optimisation (e. g. ONNX, Tensor RT, quantisation)
- Docker and containerised deployment
- CI/CD tooling (e. g. Git Hub Actions, Git Lab CI or similar)
- Monitoring and observability (e. g. Prometheus, Grafana)
- Active SC clearance xsabvtc
- Nice to have
- Edge AI deployment, ideally NVIDIA Jetson and Deep Stream
- Computer vision or video pipelines (e. g. GStreamer)
- Kubernetes, Kubeflow, Metaflow or similar orchestration tools
- Kafka or other event-driven architectures
- Data versioning tools (e. g. DVC, Deep Lake)
- Experience with imagery, geospatial or sensor data
- Previous defence, government or security-sector programmes
- MSc or Ph D in Computer Science, ML or a related field, or equivalent commercial experience
...
Machine Learning Engineer employer: SR2 Careers
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact large-scale IT and digital transformation projects. With a strong focus on employee growth, you will have access to continuous professional development opportunities while enjoying the flexibility of hybrid working in the vibrant city of London. This role not only provides competitive compensation but also places you at the forefront of cutting-edge technology initiatives, making it an exciting and rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Get Involved in Open-Source Projects
Diving into open-source projects is a brilliant way to showcase your skills and connect with other developers in the community. Not only will you beef up your GitHub profile but you might also catch the eye of someone at SR2 Careers who values hands-on experience over just theory.
✨Attend Local Tech Meetups
Tech meetups are gold mines for networking and discovering job opportunities, especially in the fast-paced world of software engineering. Check out local listings for events in your area and don’t shy away from introducing yourself. This could lead directly to a temporary position at SR2 Careers!
✨Showcase Your Work Online
With temporary roles, it’s all about standing out in a short space of time. Create a portfolio website where you highlight your projects and skills. Talk about your code, and provide links to your GitHub repositories. This will not only demonstrate your abilities but will also make it easier for recruiters at SR2 Careers to see what you bring to the table.
✨Leverage Temporary Job Boards
Don’t forget to check specialised job boards for temporary software development roles. Websites like We Work Remotely or Remote OK often list short-term gigs that can be a perfect fit. Apply directly through our website as well, making sure your application is sharp—temporary roles can move fast!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Tech Skills:Make sure your CV highlights your tech stack and any programming languages you’re proficient in. Include specifics about any frameworks or technologies you’ve worked with; they can make you stand out in the sea of applicants. It’s all about showing that you have the chops we need at SR2 Careers!
Portfolio 2.0:Since you’re applying for a temporary gig, it’s super important to showcase a portfolio that highlights your best projects. Include links to GitHub or any personal projects that demonstrate what you can do in a real-world environment. This gives us a taste of your style and your problem-solving approach!
Keep It Brief and Relevant:With a temporary position, we want to see your ability to hit the ground running. Be concise in your CV and cover letter; stick to experiences that directly relate to the role. Highlight any previous temporary roles or freelance gigs that show your adaptability and quick learning!
Tailor Your Cover Letter:Don’t just send a generic cover letter. Personalise it for Machine Learning Engineer at SR2 Careers! Mention why this temporary role excites you and how you see yourself contributing in the short run. Show us what you've got and why you're the one for this quick turn-around!
How to prepare for a job interview at SR2 Careers
✨Nail the Technical Skills
For a software engineering role, you'll likely face technical questions or coding tasks during your interview. Brush up on the relevant programming languages and frameworks that SR2 Careers uses, and don’t forget to practice some coding challenges on platforms like LeetCode or HackerRank. Showing your coding prowess can really make you stand out!
✨Prepare for System Design Questions
Even for a temporary role, having a grasp of system design principles can be crucial. Be ready to discuss how you would architect a software solution, including discussing trade-offs, scalability, and performance considerations. Having examples from previous projects can really show off your analytical thinking.
✨Demonstrate Your Adaptability
Since this is a temporary role, you'll want to emphasise your ability to hit the ground running. Highlight experiences where you quickly adapted to new technologies or teams. Let’s make it clear to the interviewers at SR2 Careers that you can learn on the job and deliver results in a short timeframe!
✨Show Off Your Portfolio
Make sure to have a portfolio or GitHub ready showcasing your projects. Having tangible evidence of what you've done—be it personal projects, contributions to open-source, or previous work—can convey how capable you are. Tailor this for what might interest SR2 Careers, so it's relevant and sparks conversation during your interview.
