Machine Learning Engineer — Production AI & Safety

Faculty Science Limited; Greater London; Hybrid; GBP 75,000 - 110,000; Full time

Benefits offered by this job

Unlimited Annual Leave Policy

Private healthcare and dental

Enhanced parental leave

Family-Friendly Flexibility & Flexible

Sanctus Coaching

Hybrid Working

Job summary

Faculty Science Limited is seeking a Machine Learning Engineer to bring production-grade ML solutions to real-world client projects. You will help design scalable software architectures, validate technical feasibility, and ensure timely delivery of high-quality ML systems in collaboration with cross-functional teams.

The role requires hands-on experience with ML lifecycles, Python, cloud platforms, and container orchestration, along with the ability to communicate complex concepts to both

Qualifications

• Understanding the full ML lifecycle and operationalising models.
• Strong Python skills and software engineering practices.
• Experience with cloud platforms (AWS/Azure/GCP) and security.
• Hands-on experience with container/orchestration tools (Docker, Kubernetes).
• Solid grasp of probability, statistics, and common ML techniques.
• Excellent communicator capable of guiding technical teams and explaining ML to non-technical stakeholders.

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 feasibility and impact.
• Define and implement Faculty’s standards for deploying ML at scale.
• Act as a technical advisor to customers and partners, translating ML concepts for stakeholders.

Skills

ML lifecycle

Python

Cloud platforms

Docker & Kubernetes

Statistics & ML concepts

Communication

Autonomy

Tools

Docker

Kubernetes

Job description

Faculty Science Limited is seeking a Machine Learning Engineer to bring production-grade ML solutions to real-world client projects. You will help design scalable software architectures, validate technical feasibility, and ensure timely delivery of high-quality ML systems in collaboration with cross-functional teams.

The role requires hands-on experience with ML lifecycles, Python, cloud platforms, and container orchestration, along with the ability to communicate complex concepts to both