At a Glance
- Tasks: Lead the delivery of production ML platforms and drive MLOps best practices.
- Company: Major organisation investing heavily in AI and Machine Learning.
- Benefits: Competitive day rate, hybrid work model, and potential for contract extension.
- Other info: Opportunity to work with multidisciplinary teams and enhance your career in tech.
- Why this job: Join a dynamic team and shape the future of AI with your leadership skills.
- Qualifications: 6+ years in a leadership role with strong Python and MLOps experience.
The predicted salary is between 63000 - 77000 £ per year.
Job Description
\n Tech Lead - MLOps | 6-Month Contract (Extension Likely) \n
Hybrid
Two days on-site every other week
Day Rate
Competitive, inside IR35 \n We're supporting a major organisation investing heavily in AI and Machine Learning, looking for an experienced
Tech Lead to lead the delivery of production ML platforms. \n This is a leadership role, owning a product area and leading multidisciplinary teams across Software Engineering, Data Engineering, Dev Ops and Data Science while driving MLOps best practice.
- You'll need: \n \n
- \n
6+ years in a Tech Lead, Engineering Manager or similar leadership role.
- \n
Experience leading engineering teams of 15+.
- \n
Strong Python and Type Script experience.
- \n
Recent hands-on MLOps experience across the full ML life cycle.
- \n
AWS experience.
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Knowledge of ML platforms such as Sage Maker, MLflow or similar.
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Strong stakeholder management and technical leadership skills.
\n \n This role is suited to someone with recent end-to-end MLOps experience, from model training and deployment through to monitoring and operational management, rather than a purely Gen AI or LLM-focused background.
MLOps Technical Lead in London employer: Xpertise
Join a dynamic team in Glasgow as an iOS Developer, where innovation meets collaboration. We offer a supportive work culture that values professional growth and provides opportunities for skill enhancement through hands-on experience with cutting-edge technologies. Enjoy the flexibility of a contract role with the potential for extension, all while being part of a company that prioritises employee well-being and development.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Technical Lead in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Xpertise before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Xpertise.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Xpertise.
We think you need these skills to ace MLOps Technical Lead in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Xpertise, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Xpertise, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Xpertise’s attention and show the tangible impact of your work.
How to prepare for a job interview at Xpertise
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Xpertise.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Xpertise.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Xpertise.
