Production ML Engineer — Responsible AI & Impact

Fdetimes; Greater London; Hybrid; GBP 70,000 - 120,000; Full time

Job summary

Faculty is seeking a Machine Learning Engineer to deliver bespoke, production-grade AI solutions for diverse clients. You’ll bridge research and real-world impact by building scalable ML systems, collaborating with cross-functional teams, and reinforcing leadership in practical AI safety.

You’ll work with Python, cloud platforms (AWS/Azure/GCP), Docker and Kubernetes, and ML frameworks such as Scikit-learn, TensorFlow or PyTorch.

Qualifications

• Experience building LLM applications.
• Strong Python skills.
• Experience with cloud platforms and infra (AWS/Azure/GCP).
• Experience with Docker & Kubernetes.
• Knowledge of ML concepts and lifecycles (scikit-learn, TensorFlow, PyTorch).
• Excellent communication skills to translate ML concepts for stakeholders.

Responsibilities

• Build and deploy production-grade ML software and infrastructure.
• Create reusable, scalable ML solutions for testing Frontier AI models.
• Collaborate with engineers, data scientists, and commercial leads to solve client challenges.
• Lead technical scoping and architectural decisions for feasibility and impact.
• Define and implement Faculty’s deployment standards for ML at scale.
• Act as technical advisor, translating ML concepts for stakeholders.

Skills

Python

LLM apps

Cloud platforms

Docker

Kubernetes

ML frameworks

Communication

Job description

Faculty is seeking a Machine Learning Engineer to deliver bespoke, production-grade AI solutions for diverse clients. You’ll bridge research and real-world impact by building scalable ML systems, collaborating with cross-functional teams, and reinforcing leadership in practical AI safety.

You’ll work with Python, cloud platforms (AWS/Azure/GCP), Docker and Kubernetes, and ML frameworks such as Scikit-learn, TensorFlow or PyTorch.