You will use Azure Databricks, Azure Data Factory, Azure Data Lake Storage Gen2, and Azure SQL/PostgreSQL; develop in Python, Scala, and SQL; and work with Spark, CI/CD, Git, and Docker to build data pipelines. These solutions support HR and employee lifecycle processes within the company.

Methods Business and Digital Technology★4.5 (2)· London

Design, build and improve ETL/ELT pipelines using SQL, Python, Apache Spark (PySpark/Spark SQL), Azure Data Factory or Airflow, Docker, and CI/CD. You will support client engagements to stabilise business-critical processes and establish repeatable data foundations across enterprise systems, working with data from Ariba, Workday, or SAP S/4HANA.

Build and maintain integrations between HubSpot, People Planner, and BigQuery using Python, SQL, REST APIs, and GCP tools (Cloud Run, Cloud Scheduler, Secret Manager, GitHub Actions). You'll own data flow for a media agency's operational systems, keeping data structured and synced into Notion for client teams.

T. Rowe Price★3.6 (709)· London

Work with SQL, Python, data warehouses, analytical platforms, UML, Jira, and Confluence to define and deliver strategic investment data capabilities for portfolio management, research, trading, analytics, and AI within the Investment Data Strategy & Architecture team at a global asset manager.

You will work with Python, deep learning image models, machine learning and large image and tabular datasets. The KYC Global and Onboarding Team implements ML models and systems supporting Document verification for customer onboarding. You will own the full lifecycle of these models and mentor junior team members.

You will design and train custom deep-learning models and fine-tune large language models using Python, TensorFlow, or PyTorch. The work involves leading research for Kangal AI, a venture building frontier AI for governments and security clients. You will own the entire model stack and scale a research team as a founding hire.

Work with Python, Nextflow/Snakemake, SMILES/SMARTS/SAFE, molecular fingerprints, LC-MS/MS data (mzML, MSConvert), and spectral databases (GNPS, MassBank, MoNA) to build schemas, QC pipelines, and datasets. You'll join Novogaia's small team creating foundation models that predict molecular structure from mass spectrometry data for natural-product drug discovery.

You'll work with Python, reproducible/containerized pipelines, cheminformatics representations (SMILES, InChIKey, fingerprints), and computational mass spectrometry. Novogaia is an applied AI drug discovery company building foundation models for molecular structure prediction from mass spectrometry data, and you'll own the design of internal benchmarks and evaluation pipelines for these models.

Glasswall★0.0· London

Work with Python, PyTorch, Scikit-learn, Hugging Face, Git, CI/CD, and MLOps tools to build, tune, and optimize machine learning, deep learning, and generative AI models. You will design LLM-powered systems (RAG pipelines, fine-tuning, agentic AI architectures) and production-grade pipelines within the Applied AI team at Glasswall. This hands-on role includes providing technical guidance and mentoring to mid-level and junior engineers.

Work with Go, Rust, Python, Java, or C++ and headless browsers (Chrome DevTools Protocol, Playwright, Puppeteer) to build large-scale web crawlers and data pipelines. The team develops infrastructure for acquiring massive amounts of public web data to train AI models, operating a distributed crawler via a bandwidth-sharing network and processing billions of videos, transcripts, and audio files.

Work with Python, Java, C++, TensorFlow, Keras, PyTorch, and optionally NLP, computer vision, and cloud platforms (AWS, Azure). The role at Demo Co. involves developing and implementing AI models and algorithms, integrating AI solutions into existing systems, and conducting research to enhance AI application performance.

You will design, develop, and productionise optimisation algorithms and decision-support tools using Python, Java, and/or Rust, employing MILP, metaheuristics, stochastic programming, or reinforcement learning. The role involves building cloud-deployed CI/CD, containerised, and orchestrated solutions for transportation, logistics, workforce scheduling, and media planning as part of cross-functional product squads. You will act as a senior technical lead, mentoring peers and driving engineering standards.

Millennium Management★3.8 (21)· London

Work with Python, C++, Docker, Kubernetes, Ceph, MongoDB, Kafka, Numpy, Polars, Scikitlearn, and Pytorch on a small, collaborative systematic trading team. The role involves developing real-time event-driven systems for alpha research, feature engineering, portfolio construction, and trade execution.

dunnhumby★3.9 (87)· London

You’ll work with Python, APIs, microservices, cloud platforms (AWS/GCP/Azure), large-scale data pipelines, and front-end code, using AI-assisted engineering tooling. As part of dunnhumby’s DNA retail media service, you’ll embed with brands, agencies, and retailers to ship production-ready software and turn field learning into product direction.

PlayStation★3.8 (164)· London

Design, build, and optimize data ingestion, transformation, and enrichment pipelines using SQL, Snowflake, Python, and REST APIs. You will join the Security Data Analytics team at PlayStation, developing data products and pipelines that help Information Security teams understand security posture and risk trends. This is an individual contributor role; no team size is stated.

The AA★3.1 (797)· London

You'll build production-ready AI applications using Python, APIs, and cloud-native services, working with Generative AI, LLMs, RAG, agentic systems, plus CI/CD, containerisation, MLOps, and LLMOps. You'll join The AA's newly established AI function, designing intelligent products for the motoring organisation's members, customers, and frontline teams.

Sumitomo Group★3.7 (463)· London

Work with SQL Server, Azure, Python, C#/.NET, JavaScript, Alteryx, Microsoft Fabric, PowerBI and DealCloud. Build backend databases, ML models and front‑end tools for the Private Markets team’s European LBO direct lending and private credit vehicles. The Data and Analytics team is adding its third key member to lead data‑platform engineering.

Millennium Management★3.8 (21)· London

Software engineers build and maintain distributed systems for intraday risk, trade, and portfolio management using Python, Java, or Rust and cloud platforms like AWS or GCP.

Lead Java Developer (Contract) role using Java 17+, Spring, Spring Boot, Azure, containerisation, serverless tech, Terraform, and Python. Building enterprise-quality optimisation and ML solutions for field operations. Leading development, API design, and tech decisions.

WPP★3.7 (378)· London

Lead Java Developer role at WPP's Satalia building a new logistics optimization platform using Java 17+, Spring, Spring Boot, Azure, serverless and containerized tech, Terraform, and some Python, with API design and tech selection duties. The team develops optimization and ML-based enterprise solutions, and the role leads a development team.

Python and C++ for developing scalable quantitative research frameworks, investigating data mining and machine learning algorithms, and modeling future price actions at a leading global quantitative trading firm that builds market prediction models.

Build trading systems, market data infrastructure, and quantitative research platforms using C++, Python, and Java. The role is with a network of 40+ top trading firms, focusing on trading platforms, risk systems, and data infrastructure for high-frequency trading.

Senior engineers at Great Yellow design and own data pipelines (ETL, dbt, SQL) and write production code in a Cloudflare-native TypeScript/React monorepo. The team builds the data and software platform that powers a system for making regenerative land-use investable and scalable.

You'll work with Python, SQL, Linux, Docker, and legacy systems, plus desirable tools like dbt, Snowflake, Kafka, AWS, and Java. You'll develop ELT pipelines, build a streaming platform for tick data, and consolidate legacy systems for Aspect Capital, a London-based systematic hedge fund. This is a lean team owning end-to-end delivery of data ingestion and transformation.

Build and maintain ETL/ELT pipelines using Python, SQL, BigQuery, REST APIs, and GCP tooling (Cloud Run, Cloud Scheduler, Secret Manager) to sync data between HubSpot, a People Planner, and Notion. The role owns the flow of operational data (client, revenue, pipeline) into the data warehouse and reverse ETL back into business systems used by Finance, Ops, and Client Leadership teams.