AL/MI Engineer

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

Job summary

Zuma Labs is a disruptive technology startup building AI/ML systems for real-world trading workflows. As an AI/ML Engineer you will design, deploy, and iteratively improve intelligent systems with broad autonomy, collaborating with founders, engineers, and traders to ship impactful ML solutions.

You will work on embedding models, RAG-style retrieval, and PEFT techniques, with a focus on rapid experimentation, measurable impact, and production readiness in a high-autonomy startup environment.

Qualifications

• Strong hands-on experience with PyTorch (Torch).
• Experience working with LLMs, embeddings, and reranking models.
• Practical experience with PEFT techniques, including LoRA adapters.
• Experience with dataset construction, cleaning, and synthetic data generation.
• Strong understanding of ML fundamentals (evaluation metrics, optimisation, generalisation, etc.).
• General understanding of supporting infrastructure: git, containers, microservices, etc.
• Comfortable working with numerical data and analytical problems (finance/trading knowledge not required).

Responsibilities

• Develop and deploy LLM-powered systems using Torch and SGLang.
• Build, fine-tune, and optimise embedding models and reranking models.
• Design and execute data curation strategies, including synthetic data generation for training and evaluation.
• Work closely with product and domain experts to translate real trading workflows into ML solutions.
• Run experiments, evaluate model performance rigorously, and ship improvements quickly.
• Contribute to infrastructure supporting training, evaluation, and production deployment.

Skills

PyTorch

LLMs

Embeddings

Reranking models

PEFT (LoRA)

Synthetic data generation

ML fundamentals

Git

Containers

Microservices

SGLang

Tools

SGLang

Git

Job description

Zuma Labs is a disruptive technology startup building force multipliers for systemic industries. Our first two products, Venetian and Squawk, target the over-the-counter (OTC) trading markets. We work closely with our customers and count a large, publicly traded brokerage among our partners. Trading technology is an old industry… and we’re here to change that. Like many startups, we value creativity, entrepreneurship, and real passion for problem-solving. But what we’re really looking for are born-and-bred hackers, people with a healthy disrespect for the status quo and the drive to build something better.

About the Role

As an AI / ML Engineer, you will work directly with the founder, engineers, brokers, and traders to design and deploy intelligent systems that have immediate real-world impact. You’ll be given broad, high-level objectives aligned with the company vision - and significant autonomy in how you execute them. We prioritise working solutions over perfect answers, rapid iteration over theory, and measurable impact over vanity metrics. We’re looking for a driven self-starter who takes confidence in their work, yet isn’t afraid to ask questions, challenge assumptions, or seek advice. Nobody has all the answers - and the strongest engineers are those who learn fastest.

Responsibilities

• Develop and deploy LLM-powered systems using Torch and SGLang.
• Build, fine-tune, and optimise embedding models and reranking models.
• Design and execute data curation strategies, including synthetic data generation for training and evaluation.
• Work closely with product and domain experts to translate real trading workflows into ML solutions.
• Run experiments, evaluate model performance rigorously, and ship improvements quickly.
• Contribute to infrastructure supporting training, evaluation, and production deployment.

Qualifications

• Strong hands-on experience with PyTorch (Torch).
• Experience working with LLMs, embeddings, and reranking models.
• Practical experience with PEFT techniques, including LoRA adapters.
• Experience with dataset construction, cleaning, and synthetic data generation.
• Strong understanding of ML fundamentals (evaluation metrics, optimisation, generalisation, etc.).
• General understanding of supporting infrastructure: git, containers, microservices, etc.
• Comfortable working with numerical data and analytical problems (finance/trading knowledge not required).

Preferred Skills

• Experience deploying ML systems into production environments.
• Familiarity with RAG architectures, prompt engineering, or hybrid retrieval systems.
• Experience building low-latency or real-time ML systems.
• Exposure to experimentation frameworks and model benchmarking.
• Cloud infrastructure and containerised ML workflows.
• Experience working in a startup or high-autonomy product environment.

Build AI systems that power real users in demanding, systemic industries. Operate in a high-impact startup environment where your work directly shapes the product. Collaborate with founders, engineers, and traders in a fast-moving, intellectually rigorous team. Work at the intersection of LLMs, real-world markets, and applied engineering - not research for research’s sake.

Equal Opportunity Statement

Zuma Labs is committed to diversity and inclusivity in the workplace.