At a Glance
- Tasks: Lead the ML/AI division and build key initiatives in cutting-edge technologies.
- Company: Join a renowned company at the forefront of machine learning innovation.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with exciting projects in search, ranking, and knowledge graphs.
- Why this job: Make a significant impact in the world of AI and machine learning.
- Qualifications: Exceptional technical skills in machine learning and leadership experience.
The predicted salary is between 72000 - 88000 £ per year.
Location: London but can support Remote working
Technology: Engineering centric Machine Learning Science / Engineering w/LLMs
One of our clients, an exceptionally well known company, are in the market for a Principal Machine Learning Engineer to join their ranks and lead their ML/AI division from a technical perspective. As a Principal Machine Learning Engineer, you will work with group relative Data and be responsible for building out some of their key initiatives across some core areas which include Search, Ranking, Knowledge Graphs, LLMs and more.
We can't go into too much detail on the specifics of the role but as a Principal Machine Learning Engineer we are looking for exceptional technical skills alongside the ability to understand product and lead from a technical capacity.
Principal Machine Learning Engineer in London employer: Burns Sheehan
As a Chief Product Officer at this dynamic PE-backed business in central London, you will be part of a forward-thinking team that values innovation and collaboration. The company offers a vibrant work culture with a strong focus on employee growth, providing opportunities to lead impactful B2B data product initiatives while enjoying the benefits of a profitable and established organisation. With a commitment to professional development and a strategic vision for the future, this role promises a rewarding career path in an exciting environment.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Machine Learning Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Burns Sheehan or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Burns Sheehan.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Burns Sheehan.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Burns Sheehan that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Principal Machine Learning Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Burns Sheehan.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Burns Sheehan and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Burns Sheehan
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Burns Sheehan uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
