Machine Learning Engineer

Stack

Responsibilities

• ▹Build and deploy production-grade ML software, tools, and infrastructure
• ▹Create reusable, scalable solutions that accelerate the delivery of ML systems
• ▹Collaborate with engineers, data scientists, and commercial leads to solve client challenges
• ▹Lead technical scoping and architectural decisions to ensure project feasibility
• ▹Define and implement Faculty's standards for deploying machine learning at scale
• ▹Act as a technical advisor to customers and partners, translating complex ML concepts

Requirements

• ▹Understanding of the full ML lifecycle, with experience operationalising models built with Scikit-learn, TensorFlow, or PyTorch
• ▹Strong Python skills and solid software engineering best practices
• ▹Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security
• ▹Experience with container and orchestration tools such as Docker and Kubernetes at scale
• ▹Comfortable with core ML concepts, including probability, statistics, and common learning techniques
• ▹Excellent communicator, able to guide technical teams and advise non-technical stakeholders
• ▹Thrives in a fast-paced environment, with autonomy to own scope, solve, and deliver

Soft skills

What we offer

• ▹Unlimited annual leave policy
• ▹Private healthcare and dental
• ▹Enhanced parental leave
• ▹Family-friendly flexibility and flexible working
• ▹Sanctus coaching
• ▹Hybrid working

About the company

Faculty's Energy, Transition and Environment unit accelerates the transition to net-zero emissions, partnering with energy operators, GreenTech startups, and national infrastructure providers.