ML Ops Engineer

About the Role

We are working with a rapidly-growing Deep Tech AI scaleup based in London as they go into an exciting new stage of expansion! The company is currently looking to expand their MLOps Engineering function and add another experienced member to the team due to their recent success in fundraising rounds.

They are on the lookout for an ML Ops Engineer to collaborate with cross-functional teams to ensure scalability and provide vital support on issues related to PyTorch.

As an ML Ops Engineer, your responsibilities will involve cross-functional work throughout the tech division of the company, tight collaboration with the Head of Engineering, primarily focusing on MLOps.

Responsibilities

• Maintain and improve infrastructural elements that are essential to production and research.
• Create automations that improve the productivity of creating and implementing machine learning models.
• Diagnose and resolve PyTorch-related problems and bottlenecks.
• Adopt DevOps procedures to guarantee testing, quality assurance, and the effective distribution of machine learning models.
• Assist the current machine learning stack by offering technical know-how and guaranteeing its smooth functioning.

Requirements

• BSc Degree in a STEM field.
• 3+ years' experience in Machine Learning or Software.
• Solid knowledge of DevOps tools, such as Docker and K8s.
• Practical experience writing Python programs at the production level.
• Driven to work in an environment that is start-up or scaleup and provides opportunity for ongoing learning and growth.