17 of 17 Permanent PyTorch Jobs in Norfolk

lifecycle of AI projects, machine learning operationalization processes Experienced with AI solutions deployment to main cloud providers Hands-on with Python and TensorFlow or PyTorch Possessing strong interpersonal, analytical, and problem-solving skills Easily translating complex concepts in clear, concise, and meaningful ways, that a non-technical audience can easily More ❯

and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving More ❯

sales. AI Engineer Required Qualifications and Skills: Proficiency in programming languages such as Python, R, or Java, with experience in AI frameworks (e.g., TensorFlow, PyTorch, Keras). Strong knowledge of data analysis, visualisation tools, and big data technologies (e.g., SQL, Hadoop, Spark). Experience with machine learning techniques, including NLP More ❯

will bring: A background in Computer Science, Artificial Intelligence, Data Science, Mathematics, or related fields Familiarity with Python programming and libraries such as TensorFlow, PyTorch, or scikit-learn is a plus Basic understanding of machine learning concepts and algorithms Interest or experience in data preprocessing, model training, and evaluation Strong More ❯

Graphs Experience with traditional ML models and feature engineering. Experience with LLMs. Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. For More ❯

ML solutions using Python, open-source tools & infrastructure Collaborate with cross-functional teams to enhance product features, based on client feedback Work with Python, PyTorch, Tensorflow, Kubernetes, Docker & cloud platforms Ideal Candidates have 5+ years of Backend (Python) Software Engineering experience in a fast-paced, high-growth, product environment Some More ❯

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 More ❯

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 More ❯

/CPU/TPU architecture Vector/Matrix/Scaler units simulation/modelling - System C/TLM/UML ML frameworks - Tensorflow/PyTorch/Python or similar DSP algorithms - FIR/IIR filters or FFT... IP design, system design, system architecture low-power, performance and optimisation Applicants must More ❯

the boundaries of what’s possible. Nice to have experience in: Reinforcement learning Large Language Models (LLMs) Optimisation methods Deep learning frameworks (e.g., TensorFlow, PyTorch) Applied AI research at scale What’s on offer: Hybrid remote work with offices in Cambridge or London The chance to publish and share your More ❯

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 More ❯

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 More ❯

teams in AI tech. What They’re Looking For Solid AI/ML experience with a strong grasp of Python & frameworks like TensorFlow/PyTorch . Strong back-end engineering skills (Python or Node.js, bonus points for React/front-end experience). Experience deploying AI models into real-world More ❯

depth expert knowledge of AI and ML technology (deep learning, LLMs and NLPs Advanced proficiency with Python and strong experience using frameworks such as PyTorch, Flask and TensorFlow Ideally experience within a senior AI/ML position within the engineering sector Proven experience of scaling AI/ML teams, hitting More ❯

training, fine-tuning, and inference APIs. Requirements 5+ years of experience building and deploying machine learning systems in production environments. Proficiency in Python and PyTorch, with a strong understanding of transformer architectures, LLMs, and multimodal generative models. Expertise in distributed training frameworks like DeepSpeed or Fully Sharded Data Parallel (FSDP More ❯

Job Title: Machine Learning Engineer Location : Fully Remote UK Job Type: 6 Month Contract + chance for extension Interview Process : Video Interviews held remotely Rate: DOE Outside IR35 A Private Equity firm are seeking a Machine Learning Engineer to join More ❯

LLVM or MLIR Work with hardware teams to ensure the software stack fully leverages the capabilities of our OTPU architecture Extend ML frameworks (e.g. PyTorch, ONNX, OpenXLA) to better support performance-critical inference paths Lead design reviews, mentor engineers, and promote best practices in HPC and performance engineering Stay on … sensitive applications Hands-on experience with ML compilers (e.g. LLVM, MLIR), and knowledge of runtime and scheduling optimisations Practical knowledge of ML frameworks like PyTorch, ONNX, or OpenXLA, and how to optimise their execution Experience scaling AI workloads across clusters or custom infrastructure—not just deploying on standard cloud setups More ❯