You will work with C++ (including memory management) and Python (Pandas, NumPy) to build high-performance infrastructure, data pipelines, and quantitative trading systems. The team develops and optimizes simulation and backtesting tools and handles high-volume market data feeds.

You will work with Python (NumPy, SciPy), C++, large datasets, distributed systems, and high-performance computing concepts. The team builds high-performance trading and analytics platforms for a HFT leader that transforms sports data into competitive insight, and you will convert prototype models into production systems and optimize for low latency and scalability.

Build high-performance trading and analytics platforms using Python (NumPy, SciPy) and optionally C++, with large datasets, numerical computing, distributed systems, and high-performance computing. The team turns complex sports data into actionable insight for a HFT leader.

Work with Python, PyTorch, scipy, scikit-learn, numpy, pandas, MLflow, Docker, Kubernetes, Ray, and GCP to build and scale distributed compute for research workloads. Phaidra creates AI-powered control systems for the industrial sector using reinforcement learning to enable facilities to learn and improve automatically.

Work with Python, NumPy, pandas, SQL, dbt, Snowflake/Databricks, and LLMs to build and deploy ML models and agentic systems (function calling, multi-agent orchestration) for Planday’s scheduling and workforce management platform. You’ll ship production features on a small, high-impact team.

Work with Python, PyTorch, and large-scale deep learning (transformers, sequence models, representation learning) to build and deploy models. As a researcher on the Options team at Citadel Securities, you turn petabyte-scale data into trading models with direct impact on options markets.

Spotify★4.1 (116)· London

Work with Python, PyTorch, NumPy, and diffusion/flow matching models for generative audio. Join Spotify's Artist-First AI Music Lab to research vocal synthesis, post-training alignment, and audio editing, creating new listening experiences for fans and artists. Conduct large-scale experiments using Spotify's infrastructure.

Trainline★3.9 (17)· London

You'll work with Python, Pandas, NumPy, Scikit-learn, Spark, Docker, Terraform, MLflow, CI/CD, and LLMs (fine-tuning, RAG, agents). The team builds production ML and AI solutions powering Trainline's search, recommendations, pricing, routing, personalization, digital marketing, and customer support across rail travel.

You'll use Python (pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow), SQL, GCP/BigQuery, MLflow, and LLM frameworks (LangChain, LlamaIndex) to build ML models for customer lifetime value, churn, fraud detection, and agentic AI workflows for myPOS's payment and commerce platform.

Deutsche Bank★3.8 (3.5k)· London

You'll work with Python, Scikit-learn, Pandas, and Numpy to develop anomaly detection models and fraud identification controls across Deutsche Bank's Investment and Corporate Bank. The TaCC team within Group Strategic Analytics builds bespoke models with global responsibility for model development, data integration, ETL/ELT processes, and production deployment across all products, businesses, and regions. You'll own problem sets, manage stakeholders, and drive growth of the codebase.

You'll work with large language models, ML frameworks like JAX/PyTorch/TensorFlow, and scientific tools including NumPy and SciPy to develop LLM applications for drug discovery. Isomorphic Labs builds AI models for accelerated drug design and molecular modeling, applying frontier AI beyond AlphaFold to unlock faster breakthroughs in medicine. Depending on experience, you may lead ML research projects, provide technical mentorship to the research community, and shape the research roadmap.

Flow Traders, a proprietary trading firm, seeks a Senior Research Engineer to lead development of their trading model research framework using Python, PyTorch, Polars, Pandas, Ray, AWS/Azure/GCP, Docker, and Kubernetes. You'll design end-to-end ML pipelines for training and deploying trading models in production, then partner with Quantitative Researchers to develop data-driven systematic trading strategies and alpha signals.