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About Quantiphi:
Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients.
Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.
Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters
We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:
Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.
We are also proud to be certified as a Great Place to Work—reflecting our commitment to our people and our culture.
For more details, visit: Website or LinkedIn Page
Role: Sr. Machine Learning Engineer
Experience Level: 5+ Years
Employment type: Full time
Location: UK
What you will do:
We are looking for an experienced Machine Learning Engineer to lead a newly formed ML Engineering team. As a ML Engineering Manager, you will play a key role in building and maintaining the infrastructure to acquire data from the data platform, deploy models, maintain, monitor and upgrade core data science services in GCP – Vertex AI (essential) and Azure (desirable) that supports the deployment of machine learning models across the enterprise. You’ll work closely with Data Scientists, Platform Engineers, and Developers to ensure seamless integration and scalable, production grade machine learning solutions.
This is a hands-on engineering manager role focused on developing APIs, infrastructure, and deployment pipelines for machine learning models. You’ll be expected to write clean, reusable code, follow best practices in cloud and software engineering, and contribute to the operational excellence of our machine learning systems.
In addition to strong engineering skills, you’ll bring a solid understanding of Data Science principles. You should be comfortable reading, questioning, and interpreting machine learning models to ensure they are deployed appropriately and effectively. Your ability to bridge the gap between model development and production deployment will be key to delivering robust, high impact machine learning solutions. You’ll be expected to understand and implement methodologies from the ML OPs life cycle.
You’ll also be expected to work in an Agile environment, contributing to iterative development cycles, collaborating across disciplines, and adapting quickly to changing requirements.
Key Responsibilities
Person Specification
To succeed in this role, you’ll typically have:
What is in for you: