You will work with scripting languages, pipelining tools, and machine learning, focusing on adversarial robustness, data influence, watermarking, and GenAI audio/video models. The team accelerates research on trustworthy, robust ML, including the provenance of synthetic media and data trustworthiness, with SynthID as a public example.

You will develop neuro-symbolic AI architectures for Project SENTINEL, an Innovate UK grant-funded initiative building provably safe guardrails for autonomous systems. Your daily work involves Python and ML libraries (PyTorch, TensorFlow, scikit-learn) to design deep learning models, NLP systems, and scalable ML pipelines for production deployment.

You will work with Python, SQL, Pandas, Snowflake, Elasticsearch, Docker, Kubernetes, Airflow, Spark, and Apache Kafka to build and maintain thousands of data ingestion pipelines and monitoring platforms. These systems feed investment decisions and model the fund’s view of the financial world.

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.

Brown-Forman★3.6 (194)· London

The Marketing Director will drive AI transformation within the marketing organization, leveraging advanced AI, the existing MarTech stack, and tools like generative AI and automated dashboards. This role defines and implements the company's marketing AI strategy across the entire marketing ecosystem, optimizing processes such as brand planning, campaign development, and media planning. The position leads and collaborates within a cross-functional AI Center of Excellence (COE).

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.

Capgemini★3.7 (11k)· London

Lead a team of AI Engineers, Data Scientists and ML Engineers designing, developing and deploying enterprise-grade AI and Generative AI solutions. You will architect and implement LLM and GenAI applications using cloud-native technologies within Capgemini’s Insights & Data practice, driving the AI/GenAI roadmap and overseeing end-to-end project delivery.

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.