Machine Learning Engineer

Dex; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

Dex, a leading quantitative research firm, is seeking a senior ML/HPC specialist in London to shape platforms for researchers. You will evaluate and integrate ML accelerators and HPC tech, and optimize inference latency and throughput to accelerate research velocity.

You will collaborate with internal experts and external vendors, designing robust architectures and moving concepts from PoCs to scalable production systems across distributed setups.

Qualifications

• Postgraduate degree or equivalent experience in ML or related quantitative field.
• Strong programming skills in Python, PyTorch and NumPy.
• Deep expertise in optimization methods, ML techniques, HPC, profiling or model inference.
• Demonstrated ability to evaluate and integrate novel ML/HPC technologies with vendors.

Responsibilities

• Evaluate and integrate cutting-edge ML accelerators and HPC technologies.
• Optimize model inference for extremely low latency and high throughput.
• Benchmark distributed training setups and analyze networking/storage trade-offs.
• Engage with technology vendors to influence product roadmaps and roadmaps.

Skills

Python

PyTorch

NumPy

Optimization

HPC

Education

Postgraduate degree in ML or quantitative field

Tools

ML Accelerators

Distributed Systems

Job description

A leading quantitative research firm applies scientific clarity to the most complex problems in finance. They build next-generation machine learning and high-performance computing platforms, turning novel research into tradable signals.

This role sits at the intersection of advanced ML and HPC architecture, shaping the platforms and tools that empower quantitative researchers. You won't be building models in isolation; instead, you'll evaluate, integrate, and optimize the underlying technologies that amplify research velocity, working closely with both internal experts and external vendors.

The work

• Evaluate and integrate cutting-edge ML accelerators and HPC technologies.
• Optimize model inference for extreme latency and throughput requirements.
• Benchmark distributed training setups, understanding networking and storage trade-offs.
• Engage directly with leading technology vendors, influencing their product roadmaps.
• Design and implement solutions, from rapid proofs-of-concept to robust system architectures.

What You Bring

• A postgraduate degree in Machine Learning or a related quantitative field, or equivalent commercial experience building ML systems at scale.
• Strong object-oriented programming skills, particularly with Python, PyTorch, and NumPy.
• Deep expertise in at least one of: advanced optimization methods, modern ML techniques, high-performance computing, profiling, or model inference.
• A demonstrated ability to evaluate and integrate novel ML/HPC technologies, engaging with external experts and vendors.