Research, develop, and evaluate state-of-the-art deep learning models for volumetric CT data using Python and PyTorch. You will contribute to self-supervised pre-training of large 3D foundation models and specialize models for segmentation, classification, and regression to support clinical-trial and real-world evidence programmes. The role is within the Machine Learning function at Qureight, which builds an AI-powered imaging platform for lung and heart disease.

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.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

Work with LLMs and vision models, fine-tuning, prompt engineering, and TypeScript. Develop and refine core models powering automated AML and KYC workflows for a YC S24-backed startup automating financial crime compliance.

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 and modern deep learning frameworks to develop and train models for face verification, liveness, and attack detection. You will drive research projects in computer vision and machine learning for iProov's biometric identity assurance systems, prototyping new products and improving data and evaluation strategies.

Work with AWS, Kubernetes, Slurm, PyTorch, and distributed training frameworks to build foundation model AI for physical intelligence, enabling robots to learn tasks from a single human demonstration. This hands-on role focuses on GPU compute optimisation, cluster scheduling, and high-performance networking within a small, elite team in London.

You will work with Python and PyTorch to build production-quality computer vision and deep learning models. The team develops platforms that make physical environments safer and more intelligent using real-time AI. You will own research from problem formulation to deployment, publishing at top venues and shipping at scale.

You will work daily with AWS, Kubernetes, Slurm, PyTorch and distributed training frameworks to optimise GPU compute, cluster scheduling and high-performance networking. The team is building foundation-model AI for physical intelligence, creating a system that lets robots learn complex physical tasks from a single human demonstration.

PyTorch, Kubernetes, AWS, Python, and high-performance computing power large-scale distributed training infrastructure. The founding role builds systems for a robotics AI that learns complex tasks from a single demonstration, scaling across hundreds of GPUs while optimizing throughput and infrastructure costs.

You will work with Python, PyTorch, TensorFlow, MLOps, CI/CD, and cloud-based AI systems. You will lead the technical strategy for production ML systems that transform raw sports data and live video into real-time insights and personalised fan experiences. You will mentor engineers and data scientists while owning technical direction and delivery.

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.

Accenture★3.9 (29k)· London

You will work with Python, LangChain, LangGraph, AutoGen, FastAPI, REST APIs, vector databases, Git, CI/CD, and cloud platforms (Azure, GCP, or AWS) to build, deploy, and iterate on machine learning and generative AI solutions for clients across industries.

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.

You will work with Python, PyTorch, and geometric deep learning methods (e.g., NeRF, SLAM, VIO, feature matching) to build scene matching, geo-registration, and 3D reconstruction systems for defence AI. The team specialises in scene understanding and localisation, delivering AI capabilities for machine perception and human decision-making under real-world hardware and adversarial constraints.

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.

9fin★0.0· London

You'll work with open-weight LLMs (Llama, Qwen, Mistral, Gemma), fine-tuning techniques, synthetic data generation, and AWS infrastructure to build domain-specific financial models. 9fin provides an AI platform for global debt markets, serving 300+ institutions with proprietary credit data and workflows. You'll lead end-to-end model development, improve model performance on financial and legal tasks, and collaborate cross-functionally in a fast-paced startup environment.

You'll work with Python, C++, and related languages to develop world models, 3D/4D scene representations, and robotic planning systems at Reka, an AI research lab building foundational intelligence for physical world applications including robotics, wearables, and media. The role involves collaborating with ML researchers on multimodal generative models and hardware teams to ensure sim-to-real performance across robotic platforms.

You'll develop world models, foundation models, and reinforcement learning systems using Python and PyTorch, focusing on areas like diffusion-based generative modeling, spatial AI, and multimodal learning. Wayve builds embodied AI software and foundation models that enable autonomous vehicles to perceive and navigate complex environments without maps. The role requires 3+ years deploying ML systems in production, a PhD or Master's in ML/Computer Vision/Robotics, and publications at top-tier conferences.

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.