Machine Learning Engineer

Dex; Greater London; Vor Ort; GBP 90.000 - 120.000; Vollzeit

Zusammenfassung

Dex, in partnership with leading quantitative research firms, seeks an engineer to bridge ML research and HPC platforms. You will evaluate and integrate cutting-edge ML/HPC technologies, shaping platforms used by researchers to accelerate insights.

The role emphasizes practical implementation: optimize inference latency, benchmark distributed training, and collaborate with external vendors to influence roadmaps, delivering robust architectures from proofs-of-concept to production systems.

Qualifikationen

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

Aufgaben

• 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.

Kenntnisse

Python programming

PyTorch

NumPy

ML optimization

HPC

Model inference

Ausbildung

Postgraduate degree in ML

Jobbeschreibung

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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