101 to 125 of 200 PyTorch Jobs in England

privacy-first mission Required Qualifications 2 to 5 years of experience optimizing and deploying ML models in production environments Strong software engineering background with production experience Extensive experience with PyTorch or other modern ML frameworks Experience training custom models from scratch Experience with model optimization and inference frameworks (e.g., vLLM, ONNX Runtime, Nvidia Triton) Familiarity with MLOps practices & Kubernetes and More ❯

tuning/distillation of large-scale language models, with hands-on expertise in SFT, PPO, and reward modeling. Deep proficiency in Python and AI/ML frameworks such as PyTorch, LangChain, LangGraph, GraphRAG, and AutoGen. Experience with modern vector and graph databases (e.g., ChromaDB, Neo4j) and LLMOps platforms (e.g., Azure, Databricks, Azure OpenAI). Proven track record of delivering scalable More ❯

Are you passionate about solving complex problems with data? Join a fast-growing tech and software innovation company in the heart of London. We’re looking for a Data Scientist eager to apply advanced modelling, analytics, and machine learning to More ❯

Start-up/Scale-up Experience Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Experience in automating deployments and orchestrating cloud environments Nice to have: Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI/CD tools (CircleCI), and data visualisation experience. This is a unique opportunity to join a visionary team redefining AI More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

etc.) for automation. Hands-on experience with containerization & orchestration (Docker, Kubernetes, Terraform). Skilled in cloud platforms (AWS, GCP, or Azure). Bonus points for: Familiarity with ML frameworks (PyTorch, Jupyter). Knowledge of cloud monitoring tools (Prometheus, Grafana). Experience with cloud-based databases (RDS, Aurora, Redshift, Spanner, etc.). Exposure to CI/CD pipelines (e.g., CircleCI). More ❯

statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯

databases and data warehouses. You'll be proficient in Python, R, or other relevant programming languages and have Experience with machine learning libraries and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch). With a background in data mining and pattern recognition you'll be an expert in statistical modelling, predictive analytics and regression techniques. An industry certification in data science or More ❯

Master's, PhD or equivalent experience in a technical field (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering). Python programming in a modern deep learning framework, e.g. PyTorch or JAX. Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory More ❯

developing and deploying perception algorithms (e.g., object detection, segmentation, tracking, SLAM, multi-sensor fusion) in real-world applications Proficiency in Python and C++ Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and MLOps tools/platforms Communication, interpersonal, and collaboration skills for working in a dynamic, cross-functional environment Company Statements Equal Opportunity Rivian is an equal opportunity employer and More ❯

record of high-quality research, evidenced by publications in reputable scientific journals or conferences. Expertise in software development and programming in Python. Experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow. Excellent ability to communicate complex ideas clearly, both verbally and in writing, and to work effectively within a multidisciplinary team. Strong analytical and critical thinking More ❯

research focus (PhD or MSc with equivalent industry experience) Experience working with LLMs, speech technologies (ASR, TTS), or multimodal systems Strong programming skills in Python, with experience in using PyTorch Hands-on experience with training and fine-tuning ML models, including setting up experiments and evaluating results Ability to read, interpret, and implement techniques from recent academic papers into practical More ❯

machine learning systems Qualifications Strong understanding of machine learning principles, especially in the context of LLMs. Solid proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch Experience with large-scale data infrastructure Strong verbal and written communication skills with the ability to work effectively across internal and external organisations and virtual teams. Would be a plus More ❯

bring: Degree in Engineering, AI, Computer Science, Data Science, or a related field. Foundations in machine learning and computer vision. Strong Python skills with frameworks/tools such as PyTorch, TensorFlow, and OpenCV. Knowledge of version control (Git) and collaborative software practices. Problem-solving ability, adaptability, and a collaborative mindset. Wage: $35-47.50/hour (Intermediate), any hours worked More ❯

bring: Degree in Engineering, AI, Computer Science, Data Science, or a related field. Foundations in machine learning and computer vision. Strong Python skills with frameworks/tools such as PyTorch, TensorFlow, and OpenCV. Knowledge of version control (Git) and collaborative software practices. Problem-solving ability, adaptability, and a collaborative mindset. Wage: $35-40/hour (Entry Level), any hours worked More ❯

such as stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to automate and enhance geological More ❯

Solid understanding of data structures, algorithms, and software design principles PREFERRED QUALIFICATIONS Understanding of AI model optimisation techniques Experience with large language models (LLMs) Familiarity with machine learning frameworks (PyTorch, TensorFlow) Experience with AI/ML deployment platforms (Amazon Q) Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need More ❯

ability to communicate to a range of audiences. Nice to Haves Proficiency in a systems programming language (e.g., Go, C++, Java, Rust). Experience with deep learning frameworks like PyTorch or TensorFlow. Experience with large-scale data processing engines like Spark and Dataproc. Familiarity with data pipeline tools like dbt. Benefits Flexible Working Hours & Remote-First Environment - Work when and More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

/AI/Computer Vision. Exceptional Master's candidates with extensive research experience will also be considered. Strong foundations in Machine Learning, Computer Vision, and Deep Learning Proficiency in PyTorch and Python First-author publications in top-tier conferences/journals (ICML, NeurIPS, ICLR, CVPR, ECCV, AAAI, IEEE TPAMI, or similar) Preferred Experience (in at least one area) Generative AI More ❯