26 to 50 of 69 PyTorch Jobs in Cambridgeshire

models on GPUs , including transformer and VAE architectures. Experience with spatial and single-cell data modelling and their application to biological questions. Strong programming skills in Python, TensorFlow/PyTorch, and familiarity with AWS cloud infrastructure. Demonstrable track record of applying AI to solve complex biological challenges and translate outputs into biologically meaningful hypotheses. C ompetencies and Behaviours A team More ❯

also being able to work independently, define goals and scope and lead your own development effort. KEY RESPONSIBILITIES: Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories. Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations. Develop & Optimize Models: Design and optimize deep learning … Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance. Deep Learning Integration: Proficient experienced in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch) to accelerate model training and inference, with a focus on scaling and throughput. Software Engineering: Proficient skills in Python and C++, with experience in debugging, performance tuning, and test design More ❯

on AI trends and contribute to open research Requirements: • PhD or equivalent experience in ML, AI, CS, physics, or mathematics • Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) • Solid grasp of ML techniques; independent and team-oriented mindset Preferred: • Experience in LLMs, reinforcement learning, or chip design • Familiarity with JAX and optimization frameworks #J-18808-Ljbffr More ❯

on AI trends and contribute to open research Requirements: • PhD or equivalent experience in ML, AI, CS, physics, or mathematics • Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) • Solid grasp of ML techniques; independent and team-oriented mindset Preferred: • Experience in LLMs, reinforcement learning, or chip design • Familiarity with JAX and optimization frameworks #J-18808-Ljbffr More ❯

research Requirements: PhD or equivalent experience in ML, AI, CS, physics, or mathematics Strong publication record (NeurIPS, ICML, ICLR, etc.) Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow)Solid grasp of ML techniques; independent and team-oriented mindset Preferred : Experience in LLMs, reinforcement learning, or chip designFamiliarity with JAX and optimization frameworks Why Join Us: Work on More ❯

research Requirements: PhD or equivalent experience in ML, AI, CS, physics, or mathematics Strong publication record (NeurIPS, ICML, ICLR, etc.) Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindset Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work More ❯

equivalent in a technical discipline (e.g., computer science, chemistry, physics, engineering). Strong background in machine learning, including deep learning and generative models. Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. Proficiency in Python and C++, with a collaborative mindset. Familiarity with protein structure modeling, co-folding, or related methods; knowledge of organic chemistry is a plus. Why More ❯

in CS/EE or related research experience in academia or industry We will consider various levels of experience in relevant research areas Key Skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.) Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU) Experience with distributed More ❯

with RAG (retrieval-augmented generation) and GraphRAG a big plus Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of Pytorch lightning, Git, test-driven design. Knowledge of parallel computing technologies, such as NVIDIA's CUDA platform, OpenCL, and OpenMPI. The salary range for Cambridge, UK: - Senior Scientist I, Computational Biology More ❯

in CS/EE or related research experience in academia or industry We will consider various levels of experience in relevant research areas Key Skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.) Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU) Experience with distributed More ❯

. Hands-on experience in data handling, visualization , and biological data analysis. Proficient in Python , familiar with software development best practices . Practical experience with TensorFlow and/or PyTorch . Preferred Qualifications 3+ years post-graduate experience in academia or biotech/pharma, applying ML/AI to biological datasets . Prior exposure to immunology , especially TCR/BCR More ❯

solutions to improve both speed and scale. This role involves working with a wide range of infrastructures, languages, and technologies such as Linux, Windows, AWS, Python, Rust, Node, and PyTorch, and you will be driven to learn more as required. In this machine learning-focused role, you will also be curating datasets and working with ML concepts and associated libraries More ❯

jack of all trades” in MLSys. Skills and Qualifications MS or PhD in CS/EE or equivalent experience in the industry, with key skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantisation, pruning, sparsification, etc.) Experience with deployment on embedded and mobile devices (ML inference and/or training) Experience with distributed and multi-GPU More ❯

Computer Science or relevant experience in industry (PhD would be a plus!). Experience in the development of ML/AI applications using state-of-the-art toolchains, i.e. Pytorch, TensorFlow (Plus!). Familiarity with Cybersecurity: TARA, Attack Trees, HSM architectures. Exposure and familiarity with Reliability technologies, methodologies, and standards applied to SoCs, i.e. RAS, Predictive Maintenance, BFR, HTOL, HAST More ❯

expertise in helping scientists who are not machine learning experts debug and resolve errors encountered when using popular machine learning packages such as Scikit-learn, Hugging Face Transformers, and PyTorch) Knowledge and experience of Large Language Models and their applications. The ability to communicate technical concepts effectively and enthusiastically across disciplines and to audiences with a range of technical abilities. More ❯

others to succeed. "Nice To Have": Experience in Cybersecurity technology projects (Plus!). Experience in the development of ML/AI applications using state-of-the-art toolchains, i.e. Pytorch, TensorFlow (Plus!). Experience with HW and SW Architecture Modelling. Model-Based System Engineering, ISO 15288, MagicGrid Framework, SysML 2.0 (Plus!). Exposure and familiarity with Reliability methodologies. Knowledge of More ❯

optimising solutions to improve both speed and scale. This role involves working with a wide range of infrastructures, languages and technologies such as Linux, Windows, AWS, Python, Rust, Node, PyTorch and you will be driven to learn more as required. What experience do I need: We welcome applications from engineers with strong problem-solving and creative thinking skills as well More ❯

efficiently. “Nice To Have”: A Degree in Electronics or Computer Science or relevant proven experience (PhD a plus!). Experience developing ML/AI applications using toolchains such as PyTorch or TensorFlow. Professional certifications in Functional Safety (e.g., TÜV) and Cybersecurity (e.g., CISSP, CEH, or ISO/SAE 21434 Practitioner). Exposure to reliability methodologies and standards for SoCs (e.g. More ❯

optimising solutions to improve both speed and scale. This role involves working with a wide range of infrastructures, languages and technologies such as Linux, Windows, AWS, Python, Rust, Node, PyTorch and you will be driven to learn more as required. In this machine learning focused role you will also be curating datasets and working with ML concepts and associated libraries More ❯

Key skills/experience required for the Machine Learning Engineer job: MSc/PhD in a relevant field with strong ML/deep learning foundations Hands-on experience with PyTorch or TensorFlow Expertise in model training at scale and GPU systems Knowledge of model compression and optimization techniques A background in speech recognition would be beneficial This is a great More ❯

Key skills/experience required for the Machine Learning Engineer job: MSc/PhD in a relevant field with strong ML/deep learning foundations Hands-on experience with PyTorch or TensorFlow Expertise in model training at scale and GPU systems Knowledge of model compression and optimization techniques A background in speech recognition would be beneficial This is a great More ❯

conducting experiments to study their performance. Proficiency in Python software development, demonstrated by published software projects (e.g., GitHub). Experience in developing and implementing deep learning systems (e.g., in PyTorch or JAX). Preferred: Experience working with graph data, reinforcement learning, and/or generative models. Experience with molecular data in real-world drug discovery. Track record of publications in More ❯

solutions to improve both speed and scale. This role involves working with a wide range of infrastructures, languages, and technologies such as Linux, Windows, AWS, Python, Rust, Node, and PyTorch, and you will be driven to learn more as required. What experience do I need: We welcome applications from engineers with strong problem-solving and creative thinking skills, as well More ❯

Excellent organisational skills and the ability to work as part of a team and independently. Proficiency with imaging analysis tools and programming languages including Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, and statistical analysis software such as R and SQL. Familiarity with machine learning tools and Linux High-Performance Computing platforms is highly desirable. Additional Information This More ❯

applications. Develop and deploy AI solutions using Azure Machine Learning services. Have a knowledge of top ML libraries scalable across multiple CPU’s and GPU’s. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting. Troubleshoot and resolve issues related to data processing and AI model performance. Collaborate with cross-functional teams to understand More ❯