At a Glance
- Tasks: Lead and innovate in ML Platform engineering, tackling complex challenges.
- Company: Dynamic AI scale-up transforming the industry with cutting-edge technology.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Other info: Remote role for UK-based engineers with excellent career advancement potential.
- Why this job: Join a tight-knit team and make a real impact in AI development.
- Qualifications: Experience in ML platforms, leadership skills, and a proactive problem-solving attitude.
The predicted salary is between 60000 - 80000 £ per year.
Oliver Bernard are currently working with an AI scale up client who are looking for a seasoned Senior / Lead ML Platform Engineer to join their team as part of broad expansion plans across the business.
A tight knit team who are changing the way things are done in their industry, they're looking for someone to step into their ML Platform function to lead, drive, and be autonomous in their ways of working - proactively tackling sophisticated challenges whilst transforming and scaling their efforts across Cloud Infrastructure, Containerisation and more!
To be suitable for this position, you must be capable across all of the following:
- Seniority / Leadership: Must have a strong pro-active 'builder' attitude. Be capable of breaking down business problems into a technical roadmap. Comfortable writing architectural design and then leading projects through to delivery. Have prior experience working with squads of engineers, leading more Junior team members, and coaching them on best practices. Must be a strong problem solver, always looking to tackle challenges and actively fix problems day to day.
- Hands-On Expertise: Capable of introducing, driving, and building ML practices, and shaping how these are adhered to across Platform, Infra and Software Development teams. Prior experience driving MLOps practices in Cloud driven environments (AWS). Strong hands-on experience across ML tools, as well as LLMs and emerging AI & Data technologies. Expertise in Platform teams utilising Kubernetes, Terraform, CI/CD, Linux and Monitoring tools.
- Must-Haves: Prior experience in an ML Platform role - specifically within R&D driven businesses, teams or environments. Prior experience in start-up / scale-up environments. Comfortable autonomous leader, capable of driving best practices.
This is a remote position for UK based engineers and can offer £120-160K for suitable profiles ticking all the boxes.
Senior / Lead ML Platform Engineer in Slough employer: Oliver Bernard
Join a dynamic AI scale-up that fosters innovation and collaboration, where your expertise as a Senior / Lead ML Platform Engineer will be valued and impactful. With a strong emphasis on employee growth, you will have the opportunity to lead projects, mentor junior engineers, and shape the future of machine learning practices in a supportive remote work environment. Enjoy competitive compensation and the chance to work with cutting-edge technologies while being part of a tight-knit team dedicated to transforming the industry.
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We think you need these skills to ace Senior / Lead ML Platform Engineer in Slough
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 Oliver Bernard. 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!
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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.
