302 jobs for “Software Developer cambridge”
Medtronic London £76,800 – £115,200 pa
Develops high-performance, low-latency video and AI processing pipelines for use in the operating room, leveraging hardware acceleration for capture, inference, visualisation and streaming. Works in a multidisciplinary team on robust, safe-by-design medical device software, with a strong C++17-23, multi-threading and real-time video focus.
Scale AI London
Forward-deployed full-stack engineer who partners directly with public sector clients to turn ambiguous mission requirements into production-grade AI applications. Leads architecture across React, Node.js, Python, Kubernetes and global cloud infrastructure, mentoring staff and shaping reusable platform patterns. Founding-member role on Scale's Global Public Sector team.
Wayve London
Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and delivery, plus partner and OEM relationships, while staying close to embedded Linux systems code in C++ or Python.
CrowdStrike Ireland
Builds and operates large-scale distributed data pipelines, storage and presentation layers for the Intelligence team, owning systems from design and prototyping through production operations. Works autonomously with internal analyst customers, choosing the tech stack and maintaining both new and legacy Go and Python services.
CrowdStrike Romania
Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design through prototyping, implementation and production operations. Works autonomously on a distributed remote team, gathering requirements from analysts and choosing the technology stack, with existing Go and Python codebases to maintain.
NVIDIA Cambridge
Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components for end-to-end inference. Involves mapping large-scale neural network workloads onto future hardware, working with LLVM/MLIR, and collaborating with hardware architects on codesign. Hybrid role based in Cambridge.
NVIDIA United Kingdom
Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components and mapping large-scale inference workloads onto future hardware. Works at the intersection of compilers, systems and deep learning, using LLVM/MLIR and frameworks like PyTorch and TensorFlow, and collaborates with hardware architects on codesign.
Causaly London
Design and ship ML/AI solutions end-to-end, from data exploration to deployment and monitoring, choosing between classical ML, NLP, LLM and agentic approaches. Work closely with product, design and engineering on user-facing AI features, champion model and data quality, and mentor junior engineers in a biomedical knowledge platform team.
Scale AI London
Owns large enterprise AI projects end to end, from understanding customer pain points and defining requirements through development, testing and launch. Forward deploys with client teams to build bespoke GenAI applications on the Scale GenAI Platform, leading cross-functional groups and shaping product strategy with executives.
PhysicsX New York, United States US$150,000 – US$190,000 pa
Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.
PhysicsX New York, United States US$200,000 – US$250,000 pa
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.
Searchability Manchester £90,000 – £100,000 pa
Designs, builds and optimises production-grade AI solutions focused on RAG, LLMs and agentic workflows. Works with AI Platform Engineers to develop RAG pipelines, improve retrieval, implement fine-tuning and establish evaluation frameworks, while contributing to technical decisions, code reviews and mentoring.
The University of Manchester Manchester £48,337 – £59,390 pa
Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.
University of Oxford Oxford £39,424 – £43,984 pa
Develops 3D reconstruction and multi-view data fusion methods for neonatal cranial ultrasound, validating them on data from the neonatal intensive care unit. Works at the intersection of 3D computer vision, neural rendering and medical image analysis, including physics-informed rendering models for view-dependent acoustic appearance. Based in a multidisciplinary lab alongside deep learning researchers, software engineers and neonatologists.
Holt Executive Oxfordshire £60,000 – £94,000 pa
This role involves designing and developing advanced computer vision algorithms for object detection, tracking, and 6DoF pose estimation, with a focus on integration into embedded and flight software systems. The engineer will lead verification and validation activities, support sensor selection and integration, and provide technical mentorship. Collaboration with multidisciplinary teams ensures performance and compatibility across hardware and software in autonomous systems.
