Applied AI Tech Lead — Scalable ML in Production

Ethos BeathChapman; England; On-site; GBP 110,000 - 150,000; Full time

Job summary

Ethos BeathChapman is seeking a Tech Lead, Machine Learning (Applied AI) to own the execution layer of the company's intelligence, turning research and model capabilities into reliable, scalable production systems.

You will work across the full model lifecycle—data, training, evaluation, inference and deployment—leading hands-on in a fast, high talent team and delivering production ready ML capabilities that reduce hallucination and improve product quality.

Qualifications

• Experience building and shipping ML systems in production.
• Strong understanding of large model training, fine tuning, evaluation, and inference.
• Experience with API design (REST/gRPC).
• Ability to operate at the intersection of research and production.
• Proven software engineering and systems fundamentals.

Responsibilities

• Own end-to-end ML systems powering the company, from data and training through to evaluation, inference, and deployment.
• Build and evolve training and fine tuning pipelines for large models.
• Design evaluation systems that measure capability, robustness, safety, and real world product performance.
• Architect high performance inference systems, optimising latency, GPU utilisation, memory, cost, and reliability.
• Establish reliable production infrastructure for deploying, monitoring, and continuously improving models.
• Partner closely with research and application engineering to turn model capabilities into product improvements.

Skills

ML systems in production

Software engineering fundamentals

GPU based workloads

API design (REST/gRPC)

Tools

Python

Node.js

Go

PyTorch

JAX

Job description

Ethos BeathChapman is seeking a Tech Lead, Machine Learning (Applied AI) to own the execution layer of the company's intelligence, turning research and model capabilities into reliable, scalable production systems.

You will work across the full model lifecycle—data, training, evaluation, inference and deployment—leading hands-on in a fast, high talent team and delivering production ready ML capabilities that reduce hallucination and improve product quality.