60 jobs for “algorithm”
Cambridge Consultants United Kingdom
Join the AI & Algorithms department to build intelligent systems, coding hands-on and training/testing models for client projects across robotics, radar, photonics and engineering biology. Work in mixed-discipline teams attending stand-ups and planning sessions, while contributing to internal R&D that turns state-of-the-art literature into market-leading solutions and client demonstrations.
Cambridge Consultants United Kingdom
Six- to twelve-month AI and algorithms internship for PhD or Master's students, working alongside engineers on client projects involving modelling, training, testing and data wrangling. Interns also contribute to internal R&D, building on state-of-the-art AI literature, and present results to colleagues and clients. Requires strong Python, Git and demonstrable research experience, plus UK security clearance eligibility.
NVIDIA Zürich, Switzerland
Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.
NVIDIA Zürich, Switzerland
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.
Anthropic London £260,000 – £630,000 pa
Join the Pretraining team to develop next-generation large language models, working across model architecture, algorithms, data processing and optimizer development. You'll lead small research projects, design and analyse experiments, and scale distributed training infrastructure to thousands of GPUs, balancing research goals with practical engineering.
Isomorphic Labs London
Research Engineers build and optimise state-of-the-art AI models for drug design, working across the full ML lifecycle from experimentation and evaluation to production deployment. The role involves developing robust codebases, data pipelines and training infrastructure, with a focus on architectures such as Transformers, GNNs and diffusion models, in close collaboration with scientists and engineers.
Anthropic London £325,000 – £390,000 pa
Builds and operates the distributed systems that serve Claude to millions of users, spanning request routing, load balancing, autoscaling and fleet orchestration across thousands of AI accelerators in multiple clouds. The role sits at the intersection of high-performance infrastructure and ML, integrating new accelerator platforms and supporting new model architectures.
Isomorphic Labs London
Lead and contribute to core machine learning research applying large language models to drug discovery, developing and refining LLM-driven approaches across biology and chemistry problems. Work spans post-training, reasoning, test-time scaling, tool-use, alignment, agents and reinforcement learning, with model training and inference engineering in JAX, PyTorch or TensorFlow. Depending on experience, you may also lead standalone projects, mentor ML researchers and shape the research roadmap.
Wayve London
Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, interfaces and cross-team alignment. It is a principal-level leadership position mentoring engineers and setting reconstruction quality standards.
Databricks London
Owns the core write-path operations for Delta Lake, the open-source storage layer behind the Databricks Lakehouse, driving performance innovations like Low Shuffle Merge and Deletion Vectors. Involves low-level systems debugging, performance optimisation on large production clusters, architecture design, and technical leadership including mentoring and sprint planning.
Faculty London
Lead high-impact AI projects for retail and consumer clients, defining data science approaches, designing software architectures, and mentoring colleagues. Own the technical side of client relationships, scope projects, and embed responsible AI practices while delivering bespoke algorithms and production-grade systems.
MFK Recruitment Brentford £75,000 – £100,000 pa
Develop an engineering-grade spiking neural network engine for machine vision applications in defence and security contexts. Translate advanced research into robust production software using C++ and machine vision techniques. Collaborate with researchers and engineers on SNNs, CNNs, and Transformers, with integration into operational systems.
Ocado London
Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.
Cohere London
Hands-on research and engineering role on the Agent Code team, developing code-generating LLMs and autonomous agent systems for enterprise use. Involves training code models, building agent frameworks for inference and sampling, creating SFT trajectories, working on RL algorithms, and designing benchmarks, in collaboration with the pretraining team on frontier compute infrastructure.
Cohere London
Drive safety research for agentic LLMs, focusing on data generation, post-training algorithms and evaluation methods so models that access external tools and act in the world remain fair, trustworthy and secure. Work with cross-functional ML, data annotation, product and policy teams on a small, autonomous team, requiring strong statistics, software engineering and Python/PyTorch skills.
