Senior ML Engineer — AI, Cloud & Impact (Hybrid)

Senior ML Engineer — AI, Cloud & Impact (Hybrid)

Full-Time 72000 - 88000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Shape AI and data initiatives, craft Python models, and optimise ML pipelines.
  • Company: Join Datatonic, a leader in AI and cloud solutions.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic role with a focus on innovation and strategic impact.
  • Why this job: Make a real impact with cutting-edge technology and top clients.
  • Qualifications: Experience in machine learning, Python, and project leadership.

The predicted salary is between 72000 - 88000 £ per year.

Datatonic is seeking a Senior Machine Learning Engineer to shape AI and data initiatives for top clients.

You will craft production-grade Python models, optimize ML pipelines, and lead client discussions.

The role blends hands-on development with project leadership and strategic impact.

You will work across ML, data engineering, and MLOps, deploying on Google Cloud and other cloud platforms, ensuring scalable, reliable solutions that deliver real business value.

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Senior ML Engineer — AI, Cloud & Impact (Hybrid) employer: Datatonic

Datatonic is an exceptional employer that prioritises a culture of continuous learning and innovation, making it an ideal place for the Head of Learning & Development role. With a strong focus on employee growth, you will have the opportunity to shape global learning strategies while collaborating with top-tier talent in a vibrant environment. Located in London, you will benefit from being part of a fast-growing, award-winning consultancy that values your contributions and fosters a supportive community.

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Contact Details:

Datatonic Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior ML Engineer — AI, Cloud & Impact (Hybrid)

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 Datatonic 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 Datatonic.

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 Datatonic.

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 Datatonic 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 Senior ML Engineer — AI, Cloud & Impact (Hybrid)

Machine Learning
Python
ML Pipeline Optimization
Project Leadership
Client Communication
Data Engineering
MLOps

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 Datatonic.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Datatonic 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 Datatonic

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 Datatonic 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.