Senior ML Engineer – Production Systems & Impact

AI Startups UK; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Unlimited Annual Leave Policy

Private healthcare and dental

Enhanced parental leave

Family-Friendly Flexibility & Flexible

Hybrid Working

Sanctus Coaching

Job summary

Faculty is seeking a Senior Machine Learning Engineer to lead development and deployment of scalable AI systems for diverse clients. You will design production-grade ML software and robust infrastructure, ensuring ethical and operational standards are met.

The role blends technical leadership with client-facing responsibilities, requiring strong Python skills, ML lifecycle expertise, and experience with cloud platforms and container orchestration.

Qualifications

• Strong understanding of the full ML lifecycle and operationalising models.
• Hands-on experience with production-grade ML systems and tooling.
• Proficiency in Python and scalable software engineering practices.
• Experience with cloud platforms and container orchestration.
• Excellent communication with technical and non-technical stakeholders.

Responsibilities

• Lead development and deployment of scalable ML systems for clients.
• Design and implement production-grade ML software and infrastructure.
• Define best practices for deploying ML at scale across the business.
• Collaborate with engineers, data scientists, product managers and commercial teams.
• Mentor junior engineers and shape engineering culture.
• Act as a trusted technical advisor to customers and partners.

Skills

TensorFlow

PyTorch

Python

Cloud platforms

Docker

Kubernetes

Ownership

Communication

Tools

AWS

Azure

GCP

Job description

Faculty is seeking a Senior Machine Learning Engineer to lead development and deployment of scalable AI systems for diverse clients. You will design production-grade ML software and robust infrastructure, ensuring ethical and operational standards are met.

The role blends technical leadership with client-facing responsibilities, requiring strong Python skills, ML lifecycle expertise, and experience with cloud platforms and container orchestration.