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- Tasks: Lead innovative machine learning projects and mentor a talented engineering team.
- Company: Join Datatonic, a premier Google Cloud partner in AI and data transformation.
- Benefits: Enjoy 25 days holiday, competitive salary, and opportunities for professional growth.
- Why this job: Shape the future of AI while working on groundbreaking projects with top-tier clients.
- Qualifications: 5+ years in machine learning, strong Python skills, and leadership experience required.
- Other info: Dynamic work environment with a focus on innovation and career advancement.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Join to apply for the Principal Machine Learning Engineer role at Datatonic. Location: London, United Kingdom. Seniority level: Mid‑Senior level. Employment type: Full‑time. Job function: Engineering and Information Technology. Industry: IT Services and IT Consulting.
At Datatonic, we are Google Cloud’s premier partner in AI, driving transformation for world‑class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future‑proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
Your Mission
As a Principal Machine Learning Engineer (equivalent to a Lead Engineer in many organisations), you’ll be a visionary leader, driving technical excellence and innovation. You’ll engineer beautiful code in Python and set the standard for high‑quality engineering and best practices across production software and rapid prototypes. This is a hands‑on technical role with significant leadership responsibilities. You will lead projects, mentor junior and senior engineers, and actively drive client discussions. Your responsibilities will involve building trusted relationships with prospects, defining strategic approaches to use machine learning to solve complex problems, overseeing project scoping, and ensuring the successful, high‑impact delivery of these engagements. You will be a key voice in shaping our technical direction and fostering a culture of innovation.
What You’ll Do
- Translating Requirements: Interpret ambiguous and complex requirements, translating them into clear technical specifications and leading the development of innovative models to solve real‑world, high‑impact problems.
- Data Science: Lead and oversee ML experiments, driving the selection of appropriate programming languages and machine learning libraries, and establishing best practices for experimental design and analysis.
- GenAI: Pioneer the application of generative AI to develop groundbreaking and innovative solutions, setting technical direction and strategy.
- Optimisation: Architect and implement advanced optimisation strategies for machine learning solutions, ensuring peak performance, scalability, and cost‑efficiency across large‑scale systems.
- Custom Code: Design and implement highly tailored, complex machine learning code to meet unique and challenging business needs, often involving novel approaches.
- Data Engineering: Own and define the strategy for efficient data flow between complex databases and distributed backend systems, ensuring data integrity and accessibility for ML initiatives.
- MLOps: Establish and champion MLOps best practices, leading the automation of ML workflows, and driving advancements in testing, reproducibility, and robust feature/metadata storage solutions.
- ML Architecture Design: Lead the design and evolution of sophisticated machine learning architectures, leveraging advanced Google Cloud tools and services to build resilient and scalable platforms.
- Engineering Software for Production: Drive the development and deployment of production‑grade software for machine learning and data‑driven solutions, ensuring high standards of code quality, reliability, and maintainability.
What You’ll Bring
- Experience: 5+ years of progressive experience as a Machine Learning Engineer, with a significant portion in a leadership or consulting capacity, demonstrating a proven ability to lead complex projects and teams.
- Programming Skills: Proficiency in Python as a backend language, capable of delivering production‑ready code in well‑tested CI/CD pipelines.
- Cloud Expertise: Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.
- Software Engineering: Hands‑on experience with foundational software engineering practices.
- Database Proficiency: Strong knowledge of SQL for querying and managing data.
- Scalability: Experience scaling computations using GPUs or distributed computing systems.
- ML Integration: Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python).
- Soft Skills: Exceptional communication, negotiation, and presentation skills to effectively articulate complex technical concepts to diverse audiences, including senior leadership and clients, and to influence strategic decisions.
- Leadership: Demonstrated ability to lead, inspire, and mentor engineering teams, fostering a culture of innovation, collaboration, and continuous improvement.
Bonus Points If You Have
- Scale‑up experience.
- Cloud certifications (Google CDL, AWS Solution Architect, etc.).
What’s in It for You?
Holiday: 25 days plus
Principal Machine Learning Engineer in London employer: Datatonic
Contact Detail:
Datatonic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for those interviews by practising common questions and showcasing your projects. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and skills.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each role. Research Datatonic, understand their values, and align your skills with what they’re looking for. This shows genuine interest and can set you apart from other candidates.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re proactive and really want to be part of the team at Datatonic.
We think you need these skills to ace Principal Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Principal Machine Learning Engineer role. Highlight your experience in Python, machine learning, and leadership. We want to see how your skills align with our mission at Datatonic!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and data, and how you can contribute to our innovative projects. Let us know what excites you about working with us!
Showcase Your Projects: Include examples of your previous work that demonstrate your expertise in machine learning and software engineering. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team at Datatonic!
How to prepare for a job interview at Datatonic
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and Python programming. Be ready to discuss your past projects in detail, especially those that showcase your leadership skills and technical expertise. This role is all about driving innovation, so be prepared to share how you've done that in previous positions.
✨Showcase Your Leadership
As a Principal Machine Learning Engineer, you'll need to demonstrate your ability to lead teams and mentor others. Think of examples where you've successfully guided a project or helped a colleague grow. Highlighting your soft skills, like communication and negotiation, will also show that you're not just a tech whiz but a great team player too.
✨Prepare for Technical Questions
Expect some deep dives into technical topics during the interview. Brush up on advanced optimisation strategies, MLOps best practices, and cloud platforms like Google Cloud. You might even be asked to solve a problem on the spot, so practice coding challenges and be ready to explain your thought process clearly.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about Datatonic's approach to AI and data, their current projects, and how they envision the future of machine learning. This shows your genuine interest in the company and helps you assess if it's the right fit for you.
