Gravitas Group is partnering with an innovative AI engineering consultancy to hire a Senior MLOps Engineer. This fast-growing team specialises in helping organisations move machine learning solutions from experimentation into reliable, production-ready systems using modern open-source tooling.
This is an excellent opportunity for a strong software engineer who is curious about machine learning infrastructure and wants to work at the forefront of MLOps and AI deployment. Prior MLOps experience isn’t essential — the team values engineers who are eager to learn, experiment and develop their skills in this rapidly evolving space.
The opportunity
As a Senior MLOps Engineer, you’ll join a collaborative engineering team delivering high-impact machine learning infrastructure solutions for a range of clients. You’ll be involved throughout the full project lifecycle, from understanding customer challenges to designing and delivering production-ready ML systems.
Alongside client work, you’ll also have time dedicated to research, experimentation, and contributing technical content such as blogs or technical talks to help stay ahead in the evolving AI landscape.
What you'll be doing:
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Partnering directly with clients to understand requirements and design scalable ML solutions
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Leading the delivery of key technical components including architecture, development, and implementation
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Maintaining high engineering standards through code reviews and best practices
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Participating in agile ceremonies such as sprint planning, retrospectives, and stand-ups
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Mentoring junior engineers and supporting their technical growth
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Helping customers improve their understanding of MLOps practices
Exploring emerging tools, frameworks, and approaches within the ML ecosystem
What we're looking for:
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Ability to commute to Manchester 3 days per week
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Degree in Computer Science, Mathematics, or a related technical discipline
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Strong Python engineering experience with production-quality code
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Experience working with cloud platforms such as AWS, Azure, or Google Cloud
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Familiarity with DevOps principles and infrastructure-as-code
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Experience working in agile development environments
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Comfortable with modern development tools including Git, Linux/Unix, and Docker
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Exposure to machine learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn
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Strong communication skills and confidence working with stakeholders and teams
Previous exposure to MLOps concepts is beneficial but not required.
Due to the nature of some projects, candidates must be willing to undergo UK Security Clearance (SC level) after joining.
