Machine Learning Researcher

Dex; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Dex is partnering with a premier algorithmic market maker to hire a quantitative researcher for ML-driven alpha models. You will design and train deep learning architectures on high-frequency data, build streaming pipelines, and deploy models into live production trading with low latency requirements.

You should have a degree in a quantitative field and hands-on experience applying ML to real-time data, plus production-grade Python skills and experience with pipelines and experiment tracking.

Qualifications

• Degree in a quantitative discipline (CS/ML/math)
• Hands-on experience applying ML to real-world production problems
• Experience modeling time-series data or high-frequency streaming inputs
• Production-grade Python skills with ML infrastructure, pipelines, experiment tracking, and versioning

Responsibilities

• Design and train deep learning architectures for short-horizon forecasting on high-frequency data.
• Engineer streaming feature extraction pipelines transforming tick-level data into model inputs.
• Integrate predictive models into live production trading environments with low latency.
• Own the full modeling lifecycle: backtesting, execution analysis, and live monitoring.

Skills

Python programming

ML deployment

Time-series modeling

Production ML pipelines

Education

Bachelor's degree in CS/ML/math

Tools

PyTorch

TensorFlow

MLflow

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

This is one of the premier algorithmic market makers in digital assets, deploying high-frequency trading infrastructure across global centralized and decentralized venues. Backed by top-tier venture funds, they pair the technical execution standards of elite systematic trading shops with the flat, low-bureaucracy culture of a high-growth startup. Every model built here has immediate, direct feedback from live markets running 24/7.

You will join the quantitative research team to develop ML-based alpha models derived directly from high-frequency order book and microstructure data. This is not an academic research seat running offline experiments destined for a paper; you will build the streaming pipelines, engineer the features, and deploy your models directly into live production trading alongside quant developers. Finance experience is welcome but not required, provided your technical rigor and signal extraction instincts are world-class.

The work

• Design and train deep learning architectures for short-horizon forecasting and alpha signal extraction on high-frequency market microstructure.
• Engineer streaming feature extraction pipelines that transform raw, tick-level order book data into production model inputs.
• Integrate predictive models into live production trading environments alongside quantitative developers, ruthlessly optimizing for inference latency and reliability.
• Own the full modeling lifecycle end to end, driving backtesting, execution analysis, and real-time live performance monitoring.

What You Bring

• Degree in computer science, machine learning, applied mathematics, or another rigorous quantitative discipline.
• Demonstrated track record of applying machine learning or deep learning to real-world, production problems beyond academic coursework.
• Hands-on experience modeling time-series data, signal extraction, or high-frequency streaming inputs.
• Production-grade Python skills across the standard ML ecosystem, with direct experience building ML infrastructure for pipelines, experiment tracking, and versioning.

Why apply through Dex

Elite quantitative trading firms reject the vast majority of applications at the resume screen, making it nearly impossible to cut through the noise through standard job boards. Dex gives you direct access to high-signal ML seats in market making and briefs you on the team's live tech stack and trading dynamics before you enter the loop. You apply once and let tailored opportunities come directly to you.

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