304 jobs for “Software Developer cambridge”
NVIDIA United Kingdom
Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python, ML framework internals, and CPU/GPU architecture expertise.
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.
CrowdStrike United Kingdom
Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design and prototyping through production deployment and long-term maintenance. Works fully remotely with analysts as internal customers, choosing your own tech stack across Go, Python, SQL/NoSQL and cloud.
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.
PhysicsX Singapore
Develops high-fidelity multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches. Owns the full simulation pipeline from geometry clean-up and meshing to solver setup, HPC job scheduling and experimental validation, while building parametric CAD models and AI surrogate models to support design optimisation and customer-facing delivery.
PhysicsX London
Builds and validates high-fidelity multiphase CFD and coupled CFD-DEM models, covering geometry clean-up, meshing, simulation, post-processing and experimental validation for granular and particle-laden systems. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for ML surrogate models on cloud and HPC resources, while working on-site with customers and mentoring junior colleagues.
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.
Anthropic London £255,000 – £325,000 pa
Founding leader for Anthropic's Forward Deployed Engineering practice, hiring and developing a team that embeds with strategic enterprise customers to ship production AI applications. Player-coach role balancing technical review, architecture oversight and hands-on debugging with setting standards, building repeatable playbooks and partnering with Sales, Product and Engineering. Requires travel to customer sites 25-50% of the time.
Databricks United Kingdom
Owns and grows Databricks' public sector business across the Republic of Ireland and Scotland, inheriting an established book of strategic government accounts. Runs a consumption-led sales motion, building an Ireland-wide go-to-market plan and net-new pipeline while co-selling with AWS, Azure and Google Cloud partners.
Wayve London
You'll define and manage the technical architecture for integrating Wayve's AI Driver into OEM and Tier 1 vehicle platforms, covering software–vehicle interfaces, sensors, middleware, ECUs, timing, diagnostics and validation. The role sits between core AI architecture and customer programs, turning ambiguous requirements into interface contracts, ownership boundaries and verifiable specifications.
MFK Recruitment Brentford £70,000 – £95,000 pa
Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.
Reperio Human Capital Dublin, Ireland £388 – £474 pd
Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.
Speechmatics Cambridge
Work on complex R&D projects within a Modelling Team that trains large self-supervised speech models and deploys them to production. Involves distributed training, transformer architectures, and inference optimisation, with mentoring and cross-department collaboration.
Speechmatics London
Join the Modelling Team to train large self-supervised and transformer-based speech models, deploying them into production with strong software engineering and model-serving practices. Work on complex R&D projects, optimise inference, and mentor engineers in a hybrid London setup.
Wayve London
Owns the engineering release process for autonomous driving models, defining branching strategies, release cadence, configuration management and quality gates. Reviews model, architecture and code changes against intended outcomes, assesses evaluation results and builds CI/CD tooling and observability to deliver ML systems reliably at scale.
