AI/ML Engineer

About Zuma Labs

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.

Role Overview

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.

What You’ll Do

• Develop and deploy LLM-powered systems using Torch and SGLang.
• Build, fine-tune, and optimise embedding models and reranking models.
• Implement parameter-efficient fine-tuning pipelines (PEFT / LoRA adapters).
• 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.

Required Qualifications & Experience

• 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 Experience

• 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.

Why Zuma Labs?

• 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.