Work with Microsoft Fabric (Lakehouses, Warehouses, Dataflows, Pipelines), Azure (SQL, Data Lake, Data Factory), SQL, Python, and REST API/SFTP to build ETL/ELT solutions. You will deliver modern data integration solutions for a diverse portfolio of clients within RSM’s Global VAT Team.

Work with TensorFlow or PyTorch, Python, and related computer vision/graphics libraries on neural network architectures (convolutional, recurrent, transformer, diffusion-based). The Visual Computing Group (VCG) researches and develops generative models for game rendering and live video streaming to advance state-of-the-art runtime efficiency, visual quality, and latency.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

Work with Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

Python, FastAPI, Docker, DuckDB (nice-to-have), JSON Schema, Git, and RESTful APIs. You will design and ship ETL pipelines that transform raw bank data into the FIRE regulatory reporting standard. Suade is a regtech SaaS company automating compliance and risk solutions for financial institutions.

Work with Python, FastAPI, Docker, DuckDB, JSON Schema and Git to design, build and ship client ETL pipelines that map raw bank data onto the FIRE regulatory reporting standard. You will maintain a shared ETL framework, write validated mapping code, and mentor junior engineers at Suade, a regtech SaaS company automating compliance for financial institutions.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

You will use TensorFlow or PyTorch, Python, and CV/graphics libraries, plus 3D engines like Unreal or Unity, to develop generative models for graphics and video. As part of the Visual Computing Group, you'll design neural networks and ML for PlayStation's game rendering and live

You'll work with PyTorch, TensorFlow, XGBoost, GPUs, CI/CD and containerisation on the Search & Recommendations team, building production-grade ML systems for personalised recommendations, product ranking and AI-driven styling at ASOS, covering the full lifecycle from experimentation to deployment.

Native Kotlin and Jetpack Compose development on a consumer-facing Android app for in-store grocery trips, running on a known device inside live stores. Integrates on-device edge AI (ML Kit, TensorFlow Lite) and uses AI coding tools like Cursor or Claude Code. Reports to the Head of Android.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

You'll design and own end-to-end RAG pipelines for payments domain content using Python, Azure Data Factory, Functions, ADLS, CosmosDB, and AI Search, with CI/CD via GitHub Actions and Azure DevOps. RedCompass Labs builds AI-powered payment transformation and financial crime detection solutions, including the RedFlag Accelerator for identifying human trafficking. You'll collaborate with AI engineers and payments experts to turn regulatory documents and handbooks into a reliable retrieval layer for their proprietary multi-agent AI platform.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

Build enterprise-grade web applications using Python (Django/FastAPI), React, TypeScript, and PostgreSQL. Develop RESTful APIs, responsive UI components, and contribute to system design, CI/CD pipelines, and performance optimization.

You’ll work with Python (Django/FastAPI), React, TypeScript, PostgreSQL, REST APIs, and CI/CD. You’ll own end-to-end feature delivery on scalable, enterprise-grade web applications.

Machine learning engineers at this tech-centric prop trading firm will work with Python tools and libraries, plus ML frameworks like JAX or TensorFlow, building training and inference infrastructure. The role focuses on enhancing research workflows and designing APIs for the growing ML team, applying techniques such as neural networks, random forests, and ensemble methods.

Use Python, PyTorch, TensorFlow, scikit-learn, LLMs, NLP, and SQL to build and deploy ML models for trade surveillance. You'll enhance analytics that detect market manipulation by analyzing trader behavior and order execution. Collaborate

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.

SmartestEnergy★4.1 (15)· London

You will work with Microsoft Azure Data Platform, Microsoft Fabric, PySpark, SQL, Python, Azure DevOps, CI/CD, and Power BI to build enterprise-scale data pipelines and Data Lakehouse/Data Warehouse solutions. The team develops modern cloud-based data solutions supporting ETL/ELT processes across Medallion Architecture for SmartestEnergy’s energy digitisation and decarbonisation goals.

You will work with Python, PyTorch, TensorFlow, and causal inference tools (DoWhy, EconML, CausalML) to build production AI pipelines, APIs, and microservices. You will design and deploy behavioural, sequential, and causal AI models into Digital Twins, agentic decision engines, and intelligent automation. No team size is specified.

HSBC★4.0 (16k)· London

Work with Python, Docker, Kubernetes, Flask/FastAPI, PyTorch/TensorFlow, SQL Server/Postgres, and CI/CD pipelines to build and deploy production-grade ML and GenAI services. You will join the Growth AI programme within HSBC’s Corporate & Institutional Banking Data & Analytics, developing AI applications to identify business opportunities and mitigate client attrition.

You'll work with FastAPI, TypeScript, React, OpenAI/Anthropic, PostgreSQL, and Azure to build AI agent systems—from voice interfaces to workflow orchestration—for aircraft maintenance and manufacturing. Fleetcraft builds infrastructure that helps technicians maintain and manufacture aircraft.

You will build and maintain Python services using FastAPI and Azure Functions, design and consume REST APIs, work with MS SQL Server, and leverage Azure infrastructure. The team delivers a loan management platform for a global financial services firm, handling complex servicing workflows in a regulated environment.

Edited★2.7 (3)· London

You will work with Python, *nix, LLMs, MCP, Django, Flask, FastAPI, Elasticsearch, and SQL databases. You will build an AI chatbot with agents and tooling, and scale a large-scale retail data infrastructure on AWS and bare metal for the company's AI-driven retail intelligence platform.

bp★3.8 (5.2k)· London

Work hands-on with Python, SQL, C#, Spark/PySpark, Palantir Foundry, planlogic EOS ETRM, Stonebranch, and AWS to build and maintain backend services, RESTful APIs, front-end components, and data pipelines. You will support bp’s LNG Energy Trading and Risk Management applications, including bespoke solutions for trade capture, operations, analytics, risk, reporting, and finance. This Staff Engineer role also includes mentoring and line management of the engineering team.