The experience expected from applicants, as well as additional skills and qualifications needed for this job are listed below. Were looking for an experienced ML Ops engineer to join a newly formed team in a leading quant firm, responsible for ML Operations across a next- research platform. This is a high-impact, greenfield role where youll help design and build the future of ML infrastructurefrom how data is shared, to how models are trained, deployed, and supported in production. ML is central to the firms trading strategies, and the platform you help shape will directly empower researchers and drive real business outcomes. Expect high autonomy and deep technical challengesoff-the-shelf tools wont cut it, so youll often build bespoke solutions to handle complex interdependencies in ML workflows. The Role As part of the ML Workflows team, youll take ownership of building a mature, scalable ML research and deployment pipeline. Youll work across the full ML lifecycle, including: Ingesting and managing new datasets Building tools for distributed training and inference Creating robust deployment and production support systems Youll leverage your ML Ops experience to assess the current landscape, identify gaps, and lead the technical direction of the new platform Projects youll work on include: Implementing best-practice feature and model stores Proper versioning of features, data, and models Improving inference compute utilisation through smarter serving Building CI/CD pipelines for ML workflows Solving complex job orchestration for model training Developing tooling for robust validation, monitoring, and recovery in production Were looking for engineers who thrive on complex, open-ended challenges and want to set new standards for ML infrastructure. You should have: Significant experience in ML Ops Strong coding skills in Python A deep understanding of ML lifecycle pain points and practical solutions Experience building systems for scaling training, versioning, and deployment Bonus points for experience with distributed compute, data engineering, and orchestration frameworks (e.g. Airflow, Ray, KubeFlow). Why join? Top-tier quant finance firm with huge tech investment Competitive base salary + 50100%+ annual bonus 25 days holiday, monthly WFH allowance, and 20/day lunch budget Brand new, world-class offices in central London Surrounded by some of the sharpest minds in engineering and research If you're ready to have real influence, work on greenfield infrastructure, and shape the ML future in a top business wed love to hear from you.

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