Senior Machine Learning Ops Engineer
1 day ago
Up to 80,000 DOE + Car Allowance + Bonus
We offer two bonuses (personal performance paid quarterly and company performance paid annually) with private healthcare and dental cover and a generous pension scheme.
At Specsavers, we're transforming lives through better sight and hearing. We're trusted by millions, loved by our customers, and proud to be a place where colleagues feel they truly belong. As we continue to grow, we're investing in advanced technologies to deliver even greater value—and AI is at the heart of that journey.
Our AI & ML Engineering Team is driving innovation across the business, from supply chain and marketing to finance, audiology, and clinical operations. We build intelligent, scalable solutions that improve decision-making, enhance customer experiences, and unlock new efficiencies. Whether it's predictive modelling, recommendation engines, or GenAI-powered tools, our work is reshaping how Specsavers operates.
As an ML Ops Engineer, you'll play a pivotal role in bringing our AI solutions to life. You'll lead the productionisation of machine learning models, ensuring they're robust, scalable, and monitored effectively. You'll design and build release pipelines, maintain our Azure ML and AI services, and develop reusable code libraries that accelerate delivery. You'll be a technical authority on applying software engineering best practices to AI and ML providing mentorship within the team.
We're looking for someone with deep experience in deploying AI-powered ML solutions in cloud environments like Azure, AWS, or GCP. You'll have a strong grasp of CI/CD pipelines, infrastructure as code, and continuous monitoring for live models. You'll understand the nuances of operationalising GenAI and LLMs, and you'll have delivered real-world AI applications that drive measurable business value. Your ability to collaborate across teams, communicate complex ideas clearly, and mentor others will be key to your success.
If you're passionate about AI, excited by the challenge of scaling ML systems, and ready to lead high-impact projects that make a real difference, we'd love to hear from you.
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