You'll work with Python, PostgreSQL, MySQL, BigQuery, FastAPI, Flask, GCP/AWS, and CI/CD pipelines. You'll join the commercial performance insights squad to build data pipelines and event streams for monitoring algorithmic insurance underwriting, including Monte Carlo simulation.

Synapri★0.0· London

You will use Python, SQL, PySpark, machine learning, NLP and Generative AI to build scalable data science solutions on an Insights team. The role involves transforming customer interaction data into insights, deploying models in Azure with CI/CD, and using tools like PyTorch, MLflow, DBT and Databricks.

Staff Machine Learning Engineer role at Sony Interactive Entertainment's Visual Computing Group, working with TensorFlow or PyTorch and Python for graphics and video processing. The team designs and deploys neural networks for game rendering and live streaming R&D. Requires 7+ years experience and publications at top-tier conferences.

Build production-grade generative and agentic AI using Python, scikit-learn, TensorFlow, PyTorch, XGBoost, LangChain/LangGraph, RAG, AWS Bedrock/SageMaker, Azure, GCP, vector stores, SQL, Kubernetes, and CI/CD for the company’s product platform.

You will work with Java microservices, Spring Boot, Python, SQL, Snowflake, dbt, Airflow, LangChain, Sagemaker, and MLflow. The data science team builds ML solutions for risk-based decisioning, pricing, and operational automation in insurtech/fintech. This is a hands-on leadership role—you will lead and develop the team while setting technical standards.

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.

Escalent★3.6 (38)· London

You’ll work with Python and frameworks like Django, Flask, or FastAPI, building RESTful APIs, microservices, and data pipelines while integrating AI/ML models and LLM APIs. Tech includes SQL/NoSQL databases, AWS/Azure, Docker, Kubernetes, and CI/CD. Escalent is a data analytics and advisory firm, and you’ll develop AI-powered applications and intelligent workflows in its cloud-native environment.

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'll work with Python, LLMs, Generative AI, RAG architectures, Agentic AI, Conversational AI, Voice AI, Speech-to-Text and Text-to-Speech technologies. This role designs, builds and deploys AI-powered customer and business solutions across Conversational AI, Agentic AI, Voice AI and intelligent automation for a leading international consumer technology and digital services organisation.

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.

Capgemini★3.7 (11k)· London

Work with LLMs, vector databases, prompt engineering, multi-agent frameworks, and AWS (SageMaker, ECS, Fargate, Docker, Kubernetes) to design reusable architecture patterns and integrate GenAI into enterprise applications, APIs, and data ecosystems. The role builds AI-powered solutions for Capgemini, an AI-powered global business and technology transformation partner.

Build REST and GraphQL APIs and MCP servers in Python (FastAPI, Flask) to expose ML models from Databricks to internal apps, CRM platforms, and AI agents at RBC. Work within the Data Science team to architect the serving layer, handling contract design, authentication, and documentation.

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.

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.

Moody's★3.6 (589)· London

Lead validation of credit rating models and AI model risk management at Moody's, working with R, Python, MATLAB, SQL, and preferably C++. The MRG Quantitative Review team independently validates quantitative models and scorecards supporting credit ratings, with a focus on Generative and Agentic AI risks. Requires 10+ years in model development, validation, and risk analytics.

Chubb Insurance★3.7 (1.3k)· London

You will use Python, Hugging Face Transformers, LangChain, LlamaIndex, PyTorch, TensorFlow, Docker, and cloud platforms to build and deploy LLM, RAG, and conversational AI applications. As part of Chubb Insurance's Global Analytics team, you'll design production-ready AI solutions for business value.

You'll work with Java/JVM and Spring on the backend, React/JavaScript/TypeScript on the frontend, plus CI/CD, distributed systems, and relational/non-relational databases. You'll join Wise's Account Integrity team, building fraud-prevention and financial-crime detection systems to protect customer accounts. Wise is a global technology company for moving and managing money.