Imperial College London★4.2 (238)· London

You will work with R, Python, Stata, or SAS, plus SQL and cloud-based or high-performance computing. The role uses large-scale real-world datasets to investigate metabolic dysfunction in type 1 diabetes and develop clinical risk prediction models. You join the multidisciplinary Misra Group within Imperial’s Department of Metabolism, Digestion and Reproduction.

EPAM Systems★3.8 (703)· London

You will lead the design and optimization of scalable cloud-native data architectures using Azure Databricks, PySpark, Delta Lake, and Azure services, while implementing CI/CD with Terraform, GitHub Actions, or Jenkins. The role involves driving data strategies, mentoring engineers, and enabling AI-driven solutions with Databricks ML/MosaicML.

Design and maintain automated test suites using C

You will use Python, core ML frameworks, and post-training techniques (GRPO, PPO, RLVR, SFT, PEFT) to develop enterprise-grade coding agents. This cross-disciplinary team combines Sonar’s static analysis with LLM post-training to help customers build agents generating high-quality code meeting enterprise standards.

Imperial College London★4.2 (238)· London

You will develop machine-learning and structural-bioinformatics methods for protein design using Python, modern deep-learning frameworks, protein diffusion/flow-based models, HPC clusters, and cloud computing. This role contributes to ProteinCAD, part of the CADMUS consortium, which uses designed proteins as programmable scaffolds to organise inorganic particles for manufacturing advanced magnetic materials.

Imperial College London★4.2 (238)· London

You will work with Python, PyTorch, NumPy, SciPy, Pandas, discrete-event simulation, Anaconda and Jupyter to develop performance, cost and reliability models for distributed Foundation Model inference across Cloud, Edge and IoT tiers as part of the f-inference project. This role is in the Department of Computing at Imperial College London.

SSE PLC★3.1 (539)· London

Work with SQL, Python, Databricks and Power BI to build statistical and machine learning models. You will apply analytics and AI to assess risk, controls and assurance activities for SSE, an energy company investing in electricity infrastructure.

Support production and demo trading exchange environments using Linux, Bash, Python, SQL, and relational databases. Work with tools like Grafana, Zabbix, Splunk, Kafka, AMQ, Tomcat, and AWS (EC2, CloudWatch, S3) on the Nadex regulated derivatives trading exchange team.

You will work with Generative AI, LLMs, OpenAI, LangChain, Hugging Face, PyTorch, TensorFlow, FastAPI, Streamlit, and cloud platforms (AWS/GCP/Azure). You will design and deploy GenAI solutions—including RAG pipelines, fine-tuning, and prompt engineering—for enterprise use cases such as customer service, document automation, and knowledge retrieval on the Data Science Team at a global data and AI company.

A Core AI Engineer at LSEG designs, develops, and deploys enterprise-grade AI products and services, building agentic workflows, RAG solutions, and scalable integrations with LLMs and vector databases. The role leads technical implementation across AI initiatives, mentoring engineers and defining solution architecture. The team is transforming how LSEG operates by using AI to improve service resilience, automate workflows, and accelerate engineering productivity.

Provide application support for Charles River IMS, troubleshooting issues across investment workflows, system configurations, integrations, market data feeds, and databases (Microsoft SQL Server or Oracle). The product is an end-to-end enterprise investment management platform automating front and middle office functions for asset managers.

Wise seeks a Senior Data Engineer to join the Scalable Growth team. You will work with Python, dbt, Airflow, Kafka, and Trino/Iceberg to build and maintain data pipelines, a Customer Data Platform, and marketing infrastructure. The role involves bridging engineering and analytics while coaching other engineers.