Teams at Tower Research Capital

Develop data pipelines, build and deploy machine learning and LLM-based NLP models, evaluate model performance through experiments, and optimize or fine-tune existing models. The role requires experience with TensorFlow or PyTorch, CI/CD, MLOps, Linux, SQL, Git, Bash scripting, and Python.

Design and maintain reliable ETL pipelines for fragmented financial-market data, normalize feeds into internal models, develop relational and time-series models for multiple asset classes, and build automated reconciliation and data-quality systems. Collaborate with quantitative researchers, traders, and engineering teams to deliver scalable reference-data infrastructure. The role requires strong SQL, Python or Java, Unix and shell scripting skills, financial instrument data knowledge, analytical problem-solving, and technical documentation or reverse-engineering experience.

Designs, operates, and maintains bare-metal Kubernetes clusters and develops Kubernetes operators. The role owns developer tooling and documentation, packages and maintains platform services including streaming systems, data orchestrators, databases, and caches, and contributes to platform innovation. Candidates need an MSc or PhD in computer science, at least two years of non-academic experience, programming proficiency, systems programming knowledge, Linux administration skills, and fluent French and English.