Tech Lead Manager (Machine Learning)

Utah

Machine Learning

Permanent

Our client, an innovator in the healthcare industry, is hiring a hands-on Tech Lead Manager (Machine Learning) to join their team in Utah. The successful candidate will lead the development of the Personalization Engine, combining hands-on machine learning engineering with team leadership to build and scale production ML systems that deliver real-world impact.

Responsibilities

Take ownership of the machine learning system that powers the organization’s Personalization Engine.
Lead the end-to-end ML lifecycle, including model development, deployment, monitoring and optimization.
Ensure the platform remains reliable and scalable across millions of healthcare transactions.
Build advanced ML solutions such as ensemble models, reinforcement learning approaches and multi-armed bandit systems.
Architect and maintain high-performance MLOps infrastructure, including feature stores, data pipelines and monitoring systems.
Strengthen feedback loops so models continuously learn and improve based on real patient behaviour.
Lead, manage and mentor a team of machine learning engineers.
Carry out thorough code and system design reviews to uphold strong technical standards.
Promote a culture focused on experimentation, continuous learning and meaningful impact.
Partner closely with product and design teams to translate complex patient journey challenges into ML-powered solutions.

Skillset

At least 6 years of experience designing and deploying machine learning systems in production environments at scale.
Proven experience building personalisation or recommendation engines for consumer-facing products (e.g. fintech, e-commerce).
Strong programming capabilities in Python and SQL.
Minimum of 2 years’ experience leading teams, managing engineers or operating as a technical ML lead.
Hands-on experience across the entire ML lifecycle, including data pipelines, model development and MLOps.
Ability to translate business challenges into practical machine learning solutions.
Experience incorporating Generative AI into personalisation platforms or features is a bonus.
Broader product engineering leadership experience beyond ML-focused systems.