AL/MI Engineer

About the CompanyZuma 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 RoleAs 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.ResponsibilitiesDevelop 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.QualificationsStrong 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 SkillsExperience 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 StatementZuma Labs is committed to diversity and inclusivity in the workplace.