559 jobs for “Data Engineer”
Tenth Revolution Group
This role involves designing and building scalable data solutions on Snowflake, developing robust ETL/ELT pipelines, and creating AI-ready data products. You will work on cloud migration and data modernisation projects, collaborate with technical and business stakeholders, and contribute to CI/CD and automation initiatives.
Tenth Revolution Group
Builds and scales customer-facing data products on an Azure Databricks lakehouse, combining Spark pipelines, Unity Catalog governance and LLM features such as RAG, semantic search and recommendation engines. Acts as a bridge between product, commercial and engineering teams, mentoring juniors and shaping data monetisation strategy.
Azure Databricks · Azure · Unity Catalog +7
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter.
Python · PyTorch · Pandas +3
Lead the deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Own scoping, architecture and success metrics for data/ML systems, mentor engineers, and work on-site with customers across North America, Europe, Asia and Oceania for 3-4 weeks per quarter.
Python · PyTorch · Pandas +3
Databricks · 1001–5000 people · Late stage
Leads and scales the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. Combines people leadership and hiring with executive customer advisory work, owning OKRs for revenue, utilisation and references while feeding voice-of-customer insight back into Product, R&D and GTM strategy.
Databricks · AWS · Azure +7
Wayve · 11–50 people · Series A
Post-train and scale GAIA-family large video diffusion world models to generate multimodal synthetic driving data, running generation pipelines across tens of thousands of segments and optimising GPU inference. Sits between ML research and engineering, landing synthetic data into the same training stack as real driving data and measuring its impact on driving-model performance.
GAIA · GPU · KV Cache
Wayve · 11–50 people · Series A
Join a small, high-autonomy team building Wayve's Data Transfer Hub, mission-critical infrastructure moving petabytes of sensor data per day from global partners like Uber, Stellantis and Nissan. You'll design and operate large-scale pipelines in Python and Terraform, using Flyte, Kafka and Azure, with ownership of production systems and an out-of-hours on-call rotation.
Flyte · Kafka · Azure +4
Harnham - Data and Analytics Recruitment
Build and lead multimodal AI applications spanning text, audio and video, including AI-generated avatars and automated content summarisation, within a growing AI team in a tech-led media organisation. The role involves translating business needs into scalable production AI products and collaborating with a multidisciplinary data function.
Harnham - Data and Analytics Recruitment
Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.
Databricks · Spark · Kafka +2
Amazon · Public
Joins a research team advancing multimodal deep learning for consumer devices, focusing on dataset curation, annotation pipelines and automated evaluation methods such as fine-tuned LLM-as-judge. Analyses large offline and online datasets in Python to diagnose model failures and works with training, compiler and product teams to move models from prototype to production.
Python · LLM
Databricks · 1001–5000 people · Late stage
New-grad engineers join a cohort to build infrastructure and products across backend, full stack, infrastructure, databases, systems, cloud and customer-facing teams. You own the full development lifecycle — design, development, testing and production operations — with a dedicated mentor and a focus on reliability, scalability and security.
Databricks · Genie · Lakebase +4
NVIDIA · Public
Design, develop and optimise GPU/CPU-accelerated data processing libraries such as DALI and nvImageCodec, covering numerical methods, performance tuning and benchmarking across architectures. Works closely with leadership and external partners on technical roadmaps while providing technical leadership and guidance to other library engineers.
CUDA · DALI · nvImageCodec +1
NVIDIA · Public
Design, develop and optimise GPU/CPU-accelerated numerical libraries such as DALI and nvImageCodec, with heavy focus on performance tuning, benchmarking and CUDA-based parallel algorithms. The role also involves setting technical roadmaps with partners and providing technical leadership and guidance to other library engineers.
CUDA · DALI · nvImageCodec +1
M4 Partners
Hands-on product development role building and improving machine learning and AI capabilities for an in-house AI platform. Work spans information extraction, classification, retrieval, summarisation and decision support, with a strong focus on structured JSON outputs, evaluation datasets and deployment into customer applications.
AI APIs · Vector Databases · Model Context Protocol +1
OpenAI
Builds internal tools and data pipelines for lawful data access request workflows and Legal Operations, covering intake, scoping, authorized retrieval, review and audit. Involves backend services, least-privilege access, approval gates, provenance and audit trails, working closely with Legal, Privacy and Security stakeholders.
