Senior Machine Learning Engineer - REMOTE UK (Taking models from PoC into cloud systems)

Senior Machine Learning Engineer - REMOTE UK

Python, deploying models; Guide models from proof of concept to production; overseeing the full lifecycle of machine learning models; taking models into production in cloud systems; MLOps

Are you ready to harness the power of AI and data science to impact industries as diverse as satellite communications, energy management, and healthcare?

My client is looking for a Senior Machine Learning Engineer to take on a key role in transforming concepts into cutting-edge solutions, directly shaping the future of advanced technologies. This is an opportunity to lead with your expertise and see your innovations thrive across multiple high-stakes projects. Experience of taking models from PoC into cloud systems is essential.

Why You Should Apply

• Work at the intersection of AI, advanced mathematics, and real-world impact.
• Lead multiple projects with direct customer interaction and influence.
• Be a technical authority in a forward-thinking, collaborative environment.
• Mentorship and leadership opportunities, including developing the next generation of ML engineers.
• Flexible work arrangements with a mix of remote and office options.
• Enhanced leave benefits, mental health support, and a generous pension.

What You’ll Be Doing

• Build, train, and monitor robust machine learning pipelines.
• Lead model architecture and MLOps development across multiple platforms.
• Collaborate with consultants, engineers, and customers on cutting-edge projects.
• Drive model trustworthiness through confidence quantification and explainability.
• Mentor and lead teams, fostering innovation and growth.

About You

• Be able to do the job as described.
• Expertise in Python, MLOps, and cloud services.
• Experience taking models from PoC into cloud systems
• Comfortable managing multiple, complex projects simultaneously.
• A technical leader who can guide both clients and team members.
• Experience in confidence quantification and model explainability.

Please apply via the link for immediate consideration