Quantitative researchers will develop mathematical, statistical, and machine-learning models for systematic trading, working in Python, with C++ and SQL as desirable, alongside large-scale data analysis. The role spans full research-to-production, collaborating with portfolio managers and engineers at a global quantitative investment firm. No team size is stated.

Deloitte★3.9 (14k)· London

You will work with Python, NumPy, Pandas, scikit-learn, LangChain, Hugging Face, LlamaIndex, Azure Machine Learning, Foundry, Git, and Agile practices. The team is Deloitte’s Tax Digital Innovation AI & Data Studio, which researches, builds, and delivers analytics and AI-driven solutions for tax and legal clients.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

As a Senior Machine Learning Engineer on a multidisciplinary data and AI team, you will lead complex ML work end-to-end in a secure, highly regulated environment. The listing does not specify particular technologies, languages, or tools. This is a hands-on practitioner role with high autonomy, not a people-management position.

Build pipelines and models using Python, TypeScript, and Next.js to transform unstructured data into structured, queryable formats for an AI platform supporting private-equity reasoning. You will join a six-person founding technical team focused on NLP, information extraction, and representation learning.

You will work with the PyData stack (pandas, numpy, scikit-learn, XGBoost) and advanced ML methods like neural networks to build predictive models and proprietary metrics from high-frequency cricket tracking data. CricViz is a market leader in cricket data analysis, serving broadcasters, teams and gaming platforms.

You will work with Python, NumPy, SciPy, simulation modelling, optimisation under uncertainty, cloud deployment, and machine learning. The team builds an AI operating system for secure environments, taking complex scientific models from prototype to production across government and commercial programmes.

You will work with kdb+, q, Python or Java, APIs (REST, messaging), Linux, AWS/GCP, Docker/Podman, and CI/CD. You will develop, test and maintain kdb+ applications and supporting services for market data and analytics on a Client Engineering team for a FinTech leader. You will also mentor junior developers.

Use Python, scikit-learn, TensorFlow, PyTorch, and geospatial tools like QGIS and ArcGIS. As a Machine Learning Engineer at a technology consultancy, you will design, build, and deploy ML models

You will develop and deploy LLM-powered applications using PyTorch, SGLang, and PEFT/LoRA, building and fine-tuning embedding and reranking models. You will work on an early-stage platform that combines machine learning with real-world trading workflows to transform specialised financial markets. You will join a small engineering team with direct collaboration alongside founders and traders.

Senior Software Developer role in the Data team of a global energy trading house, working on data-consumption and publishing platforms using C#, .NET, ASP.NET, Angular, SQL Server, Oracle, Docker, Grafana, Kafka, Azure Service Bus, and Azure DevOps. Responsible for end-to-end delivery, mentoring, and architectural direction.

You'll work with Python, FastAPI/Django/Flask, PostgreSQL, cloud platforms (Azure/AWS/GCP), and build scalable REST APIs and data pipelines for an enterprise AI platform used by financial institutions.

Build machine learning models in Python using PyTorch or JAX, working with sparse, noisy time-series data from real industrial operations. As an early ML hire at a startup building physics-informed AI for manufacturing, you will design, train and deploy models that combine data-driven learning with physical constraints.

You will use Python, SQL, and Streamlit on an AWS data platform to clean survey data, build statistical and machine learning models (including NLP), and design interactive dashboards. As a Data Scientist II on the Data Science Consulting team, you will deliver predictive analytics solutions that optimise clients’ marketing effectiveness. You will also manage client relationships and guide more junior team members.

Use Python, SQL, and production ML pipelines for personalization and recommendations (embeddings, ranking, collaborative filtering) on Muzz, the world's largest Muslim dating and marriage app. You'll also use AI tools, conduct A/B experiments, and work with GCP (BigQuery/VertexAI). The role includes mentoring analysts and data scientists and shaping technical standards.

Senior Machine Learning Engineer building production AI systems that help UK consumers find financial products. You'll use Python, MLflow, Kubernetes, Databricks, Airflow, LangChain/LangGraph, Terraform, and CI/CD pipelines to design and deploy batch and real-time ML models, LLM-powered capabilities, and monitoring tooling. You'll work closely with data scientists, engineers, and product teams to productionise experimental models and evolve the internal ML platform.

You will work with Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, cloud data tools (ideally Azure), and large language models (LLMs) to build predictive models and identify alpha signals. You will join the data science team of a leading investment management company.

Wise★3.5 (42)· London

You will build scalable systems for business onboarding and verification using Java or JVM languages, Spring framework, JDBC, and relational/non-relational databases with CI/CD pipelines and distributed systems. This engineering team owns end-to-end projects to automate verification, create flexible onboarding journeys, and manage compliance risks for Wise’s money-moving platform across Europe and the UK.

You'll build scalable AI data pipelines, cloud-native backend systems, and microservices using Python, FastAPI/Flask/Django, SQL, AWS/Azure, Docker, and Kubernetes. The company specialises in transforming AI research into secure, scalable production systems. You will also mentor junior engineers and contribute to architecture decisions.

Lead ML engineering using Python, PyTorch, TensorFlow, MLOps (CI/CD, experiment tracking, model registries) to build computer-vision and generative-AI systems. The role delivers live-sports insights—player performance, contextual statistics, injury risk—and integrates them into personalisation engines, with mentoring of Senior and Mid-Level Data Scientists.

DataCamp★3.8 (4)· London

You will work with agentic AI systems like Claude Code, Cursor, or Replit to build AI workflows that draft, grade, and quality-check assessment content. You will own the design and production of DataCamp's assessment and certification content, collaborating with subject-matter experts and teams across curriculum, engineering, product, and marketing. This is an individual contributor role.

Design, build, and optimize analytics solutions using SQL, DBT, Power BI (DAX, RLS), GitHub, and cloud platforms (Snowflake, BigQuery, Databricks, Fabric). You will drive data-driven marketing insights for enterprise clients, architecting data models and leading test-and-learn programs. The role also involves mentoring junior team members.

This role involves building ML models for low-data drug discovery using active learning, meta-learning, fine-tuning, uncertainty estimation, and multimodal modeling, with tools like PyTorch and JAX. The scientist will design data acquisition strategies and closed-loop workflows for Lila’s AI-driven scientific discovery systems, collaborating with drug discovery and computational teams.

LexisNexis Legal & Professional★3.6 (1k)· London

You will drive AI ideation and integrate LLMs, NLP, and machine learning into Practical Guidance editorial workflows. This global role partners with commercial, product, and engineering teams to deploy scalable content-optimization solutions across North America, UK, and Asia-Pacific.

PlayStation★3.8 (164)· London

This role involves working with TensorFlow or PyTorch, Python, and libraries for computer vision and graphics. As part of the Visual Computing Group (VCG), you will develop generative models to advance game rendering and live video streaming through neural networks and machine learning R&D.