Machine Learning Engineer

Dex; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Dex is seeking a highly skilled ML/HPC engineer to join a leading quantitative research environment. You will evaluate and integrate cutting-edge ML accelerators and HPC technologies, optimizing inference to meet extreme latency and throughput targets.

You will benchmark distributed training, understand networking/storage trade-offs, and collaborate with internal experts and external vendors to drive platform improvements from concept to robust systems.

Qualifications

• Postgraduate degree in ML or related quantitative field, or equivalent commercial experience building ML systems at scale.
• Strong Python, PyTorch and NumPy programming skills.
• Deep expertise in at least one: optimization methods, modern ML techniques, high-performance computing, profiling, or model inference.
• Experience evaluating and integrating novel ML/HPC technologies with external experts and vendors.

Responsibilities

• 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.

Skills

Python

PyTorch

NumPy

Education

Postgraduate degree in ML or related field

Equivalent commercial ML systems experience

Job description

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

The role

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.

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