Candidates: Create an Account or Sign In
Senior Machine Learning Engineer – REMOTE UK - taking models from PoC into cloud systems is essential
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