You will work with Python, SQL, PostgreSQL, Dagster, Git, and CI/CD tools like GitHub Actions, plus Docker, Kubernetes, and REST/GraphQL APIs. This computer-vision startup builds scalable data pipelines and infrastructure to power next-generation products across cloud, AI, and embedded systems.

You will own the C++17+ systems that ingest, process, and store high-rate sensor data from metal 3D printers, serving physics-informed ML inference and 3D insights in production. The work involves Python bindings (via pybind11), WebSockets, CMake, 3D geometry/meshes, and on-premise deployment. Nexus is an early-stage startup building the data and software layers for additive manufacturing of safety-critical parts.

DNEG★3.1 (36)· London

Design, build, and maintain high-performance RESTful APIs, microservices, and event-driven architectures using Python, PostgreSQL, and Redis. You will integrate generative AI models (ATMAN, VAANI) into production backends for a company operating at the intersection of enterprise Media Asset Management and generative media.

Senior Unreal C++ Developer role: work with Unreal Engine 5, C++/Blueprint integration, shader development, Unreal Insights, RenderDoc, and Visual Studio to build high-performance backend systems for an iGaming platform, providing technical leadership and mentoring.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

Work with AWS, Kubernetes, Slurm, PyTorch, and distributed training frameworks to build foundation model AI for physical intelligence, enabling robots to learn tasks from a single human demonstration. This hands-on role focuses on GPU compute optimisation, cluster scheduling, and high-performance networking within a small, elite team in London.

You will architect a cloud-native backend on GCP using Python, C++, Docker, and Cloud Run, with emphasis on data-intensive or realtime systems. The deep-tech startup scales a research-led product into a production platform, collaborating with robotics/computer vision engineers to build APIs for edge devices.

Medtronic★3.8 (5.6k)· London

You will work with Python, AWS, databases, APIs, and modern DevOps tools to build distributed systems for a new Medtronic Digital Technologies product that brings connectivity, real-time guidance, and decision support to operating rooms using embedded systems and computer vision. You will own delivery, contribute to technical design, and provide mentorship to a team.

Woven by Toyota's London data infrastructure team builds ML and data pipelines using Python, Flyte, AWS, Kafka, SQS, BigQuery, and Elasticsearch to enable autonomous driving development. The team provides petabyte-scale access to vehicle fleet data for AD/ADAS perception, prediction, and validation—supporting Toyota's autonomous driving transformation across a distributed UK-US organization.

You will work daily with AWS, Kubernetes, Slurm, PyTorch and distributed training frameworks to optimise GPU compute, cluster scheduling and high-performance networking. The team is building foundation-model AI for physical intelligence, creating a system that lets robots learn complex physical tasks from a single human demonstration.

PyTorch, Kubernetes, AWS, Python, and high-performance computing power large-scale distributed training infrastructure. The founding role builds systems for a robotics AI that learns complex tasks from a single demonstration, scaling across hundreds of GPUs while optimizing throughput and infrastructure costs.

Accenture★3.9 (29k)· London

You will work with Python, LangChain, LangGraph, AutoGen, FastAPI, REST APIs, vector databases, Git, CI/CD, and cloud platforms (Azure, GCP, or AWS) to build, deploy, and iterate on machine learning and generative AI solutions for clients across industries.

Python, SQL, Dagster, PostgreSQL, Git, CI/CD (GitHub Actions), Docker, Kubernetes, and Linux. You will build scalable data infrastructure and robust pipelines for a computer vision startup transforming its industry through advanced data platforms.

Design, build, and support software for Spectacles' computer vision development using C++ and supporting infrastructure. You will focus on eye-tracking calibration, building tools and pipelines to improve reliability, quality, and validation workflows. Specs Inc. develops advanced eyewear that integrates digital experiences into the physical world.

You’ll train, debug and improve computer vision and 3D perception deep‑learning models using LiDAR, multi‑view geometry, tracking and 3D reconstruction. You’ll build scalable data pipelines with auto‑labelling to deliver ADAS perception capabilities (detection, segmentation) for real‑world driver assistance.

Axon★3.3 (126)· London

You will work with Python/C++, PyTorch, TensorFlow, AWS, AzureML, and edge hardware (Qualcomm, NVIDIA, Intel) using TensorRT, ONNX, and SNPE. As part of Axon’s CoreAI team, you will drive end-to-end development of AI systems across cloud, edge, and robotics platforms, building production systems for computer vision, NLU, multimodal AI, and GenAI.

You'll work with AWS, Kubernetes (EKS), Terraform/Pulumi, Docker, Python/Go, and edge/IoT infrastructure tools to build and maintain Coram AI's cloud-native video security platform, which uses computer vision and AI for real-time alerts and multi-site visibility. Responsibilities include provisioning AWS resources, managing large IoT device fleets, building CI/CD pipelines, and maintaining observability and compliance across edge and cloud systems.

You'll develop world models, foundation models, and reinforcement learning systems using Python and PyTorch, focusing on areas like diffusion-based generative modeling, spatial AI, and multimodal learning. Wayve builds embodied AI software and foundation models that enable autonomous vehicles to perceive and navigate complex environments without maps. The role requires 3+ years deploying ML systems in production, a PhD or Master's in ML/Computer Vision/Robotics, and publications at top-tier conferences.

JPMorgan★3.9 (20k)· London

You'll work with PyTorch, deep learning frameworks (transformers, CNNs, autoencoders), NLP techniques, Docker, cloud platforms (Azure/AWS/GCP), MLOps tools, and DAG-based pipelines to build scalable machine learning services for JPMorgan's Commercial & Investment Bank. The team develops AI-powered products that automate financial processes, enhance decision-making, and optimize business operations across the bank. This is an individual contributor role with optional management opportunities.

You'll work with Python (NumPy, SciPy, Pandas, PyTorch, JAX), C/C++, distributed computing frameworks (Spark, Dask, MPI, OpenMP, CUDA), cloud platforms (AWS, Azure, GCP), Docker, and Kubernetes to design, build, and optimize machine learning models—especially deep learning and foundation models—for PhysicsX's AI-driven simulation software stack serving aerospace, materials, energy, and automotive industries. In this research leadership role, you'll shape team strategy, set technical direction for work-streams, mentor junior engineers, and translate prototype models into production implementations at scale.

PhysicsX builds AI-driven simulation software for engineering and manufacturing across aerospace, materials, energy, semiconductors, and automotive. You'll design and optimize machine learning models using Python (PyTorch, JAX), distributed training frameworks (Spark, Dask), cloud platforms (AWS, Azure, GCP), and C/C++ for scientific computing, working with research scientists to scale foundation models and translate prototypes into production libraries and tools.

You'll work with Python, machine learning frameworks, Kubernetes, and MLOps tools to build agentic AI systems that automate customer workflows. Unitary develops AI-human hybrid solutions for trust & safety and marketplace operations, processing millions of daily images and videos at scale. You'll collaborate directly with customers to design Virtual Agents, contribute to the platform's development, and ensure production reliability while gradually building self-service tools.

You'll build and own an internal web application using React, TypeScript, and established backend frameworks, integrating with Databricks-backed workflows and internal APIs to help teams browse computer vision models and explore results. As the first dedicated fullstack hire in the Corpus & Enrichment team at Wayve—a developer of embodied AI for autonomous driving—you'll partner directly with internal stakeholders to ship an MVP quickly and iterate based on feedback.