Principal Data Engineer role using GCP, Python, Node.js, BigQuery SQL, and Jenkins CI/CD. The team enables Sky’s growth through Data and AI, deepening customer relationships, optimising commercial performance, and enhancing operational efficiency. The role provides technical leadership, managing Solution Architects and setting engineering standards.

MAREX★3.2 (6)· London

Design and implement resilient data ingestion, orchestration, and provisioning using APIs, event streaming, CI/CD, and infrastructure-as-code for Marex's enterprise data products. This role supports the firm's global financial services platform by delivering trusted, reusable data assets and integration capabilities for operational, regulatory, and analytical use cases.

Echobox★4.0 (1)· London

You will work with Python, Java, or Node.js, back-end frameworks, SQL/NoSQL databases, RESTful APIs, microservices, Git, and AWS/GCP/Azure. You will build and maintain back-end services and systems supporting AI-powered products that help online publishers.

Echobox★4.0 (1)· London

You will work with Python, Java, or Node.js, SQL and NoSQL databases, RESTful APIs, microservices, Git, and cloud platforms (AWS, GCP, Azure) to build and maintain back-end services. The company develops AI that helps online publishers like The Times and Le Monde overcome daily challenges, and you will collaborate with data scientists and product teams to support these AI-powered products.

ExxonMobil★3.9 (5.7k)· London

Work as a Full Stack Developer using Python, Node.js, React or Angular, SQL/PostgreSQL/MongoDB, and cloud platforms like Azure/AWS/GCP. You will build and maintain scalable web applications, APIs, dashboards, databases, and data pipelines to support ExxonMobil's Global Trading organization's commercial and trading activities.

Wise★3.5 (42)· London

Build backend

You will work with front-end technologies (HTML, CSS, JavaScript, React, Angular), back-end (Python, Node.js), databases (SQL, PostgreSQL, MongoDB), and cloud platforms (Azure, AWS, Google Cloud). You will design and maintain applications supporting commodity trading, market analysis, and risk management within ExxonMobil's Global Trading organization.

ExxonMobil★3.9 (5.7k)· London

Full stack developer using React or Angular, Python or Node.js, SQL/PostgreSQL/MongoDB, and cloud platforms (Azure, AWS, Google Cloud). Builds and maintains web applications, APIs, and data pipelines supporting commodity trading, market analysis, and risk management within ExxonMobil’s Global Trading organization.

LSEG★3.7 (402)· London

Use tools like Burp Suite, command-line tools, custom scripts, and automation; cloud platforms (AWS, Azure, GCP) and containerized environments (Docker, Kubernetes); and secure coding practices in Java/Springboot, .NET, JavaScript/Node, or Python. The role bridges offensive security and engineering by translating penetration test results into remediation guidance for application and platform teams within LSEG's internal offensive security team.

You'll work with PyTorch, CUDA/Triton/C++, transformer architectures, diffusion models, and audio language modelling for large-scale speech models. The Speech Team builds end-to-end TTS, voice cloning, controllable TTS, and voice conversion systems for a social AI character platform.

Build and scale real-time pipelines, analytics infrastructure, vector databases, and data workflows for an AI assistant that automates property management operations. Work with Python, Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, MongoDB, vector databases (Qdrant, Milvus, pgvector), Pandas, and Polars. This is an early data hire with input into architecture decisions.

Work with Python, C++, PyTorch, JAX, TensorFlow, and distributed training tools (DeepSpeed, FSDP, Megatron, Ray) plus GPU programming (CUDA, Triton, NCCL). You will design and optimize large-scale training and inference systems for modern ML workloads, partnering with researchers to productionize cutting-edge ideas across distributed systems, HPC, and compute infrastructure.

Beamery★4.0 (1)· London

Beamery’s Data Engineering Team builds a self-service reporting and AI data platform, ingesting multiple sources into centralized infrastructure. The Senior Data Engineer leads ETL pipeline and analytics layer development, mentors engineers, and shapes the platform underpinning the company’s talent lifecycle management solutions.

You'll work with Google BigQuery, dbt Core, Airflow, Airbyte, GitHub Actions, ThoughtSpot, Colab/Jupyter and Python. Apolitical builds products for public-sector professionals. You'll model warehouse data, define metrics, ship dashboards and own the analytics stack end-to-end as an individual contributor.

Lead Cloud Engineer role: work with Terraform, Kubernetes, Amazon Bedrock, AWS, and Infrastructure as Code; architect AI-native infrastructure including Vector Databases, RAG architectures, and production-grade Agentic Workflows. The role is with an AI-native consulting partner, delivering cloud, AI, and platform engineering projects for clients such as PayPal and adidas. You will guide and mentor a team of cloud engineers.

You will work with Python, LLMs, GenAI architectures, RAG, embeddings, vector search, AI agents, LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, Docker, Git, CI/CD, and Azure/AWS/GCP. You build and deploy production-ready GenAI and agentic AI solutions for clients, including RAG architectures and intelligent assistants. You are an individual contributor on multidisciplinary client teams, co-creating solutions from ambiguity to execution.

DeepL★3.8 (4)· London

You will work with Python, PyTorch/JAX/TensorFlow, distributed/multi-node training frameworks (FSDP, DeepSpeed), and LLM post-training methods (SFT, DPO, RLHF, PPO). You will lead research on model-steerability and reinforcement learning for DeepL’s next-generation LLM-based translation models at the scale of hundreds of billions of parameters. You will own the full lifecycle of model delivery, from prototyping and large-scale experiments to production deployment.

Deliveroo★3.3 (1.5k)· London

You will build production GenAI infrastructure, primarily working with open-weight LLMs/VLMs, GPU serving (vLLM, SGLang, TensorRT-LLM), inference engines, fine-tuning pipelines (SFT/DPO/LoRA), and Python on Kubernetes/AWS/GCP. The GenAI Platform team builds shared infrastructure—including real-time GPU serving, batch inference, the LLM Gateway, and Agent Gateway—to help Deliveroo and DoorDash teams bring GenAI-powered products and automation to production. You join a small, high-leverage team.

Deliveroo★3.3 (1.5k)· London

You'll work with LLM inference engines (vLLM, SGLang, TensorRT-LLM) and open-weight models (GLM, Qwen, Kimi, DeepSeek) on GPU serving, batch inference, and fine-tuning (SFT/DPO/LoRA), plus build the LLM Gateway, Agent Gateway, evals, guardrails, and cost attribution systems. The GenAI Platform team builds shared infrastructure to bring GenAI products, agents, and automation to production across Deliveroo, DoorDash, and Wolt.

State Street★3.4 (3k)· London

Lead this team evolving the Insights platform for Global Markets Research, building client-facing web applications using React, Angular, or Vue, with backend services in Python, Java, or Node.js on AWS cloud-native architecture (microservices, API-first, event-driven), integrating data analytics and Generative AI features.

You'll work with Python (FastAPI), Go, TypeScript, PostgreSQL, Redis, Pinecone/pgvector, AWS (ECS, Lambda, SQS), Docker, Kubernetes, Terraform, LangChain/LlamaIndex, vLLM, and Anthropic/OpenAI APIs. You'll build and optimize RAG pipelines, real-time inference APIs, and vector search infrastructure powering LLM features for 500k+ monthly active users.

Design backend services using Python, FastAPI, Node.js, Docker, Kubernetes, and cloud platforms (AWS/GCP) with SQL/NoSQL databases. You will build and evolve OneSuite, a unified marketing intelligence and automation platform powering agentic workflows, data processing, and channel automation. This is an individual contributor role.

Work with Terraform, Kubernetes, Vector Databases, Retrieval-Augmented Generation (RAG), Agentic workflows, OpenTelemetry, and Infrastructure as Code. As a consulting partner for clients like PayPal and adidas, you lead cloud-to-AI platform engineering, building autonomous platforms and managing AI lifecycles. You also mentor a team of cloud engineers.

Fidelity Investments★4.0 (5.1k)· London

Use Rust, Python, SQL/Snowflake, and blockchain data tools (The Graph, Dune) to build research infrastructure and develop yield-generating DeFi strategies. You will extend backtesting systems and implement on-chain analytics for the Quantitative Strategies team within Fidelity Digital Assets™.

Zoopla★3.9 (18)· London

Work with Python, scikit-learn, PyTorch, TensorFlow, AWS (SageMaker, ECS, Lambda, SQS, DynamoDB), and MLOps tooling to build end-to-end ML pipelines. You will design and deploy production ML models that bring intelligent automation and predictive capability to the UK property market, using Alto's large dataset of real housing transactions.