151 to 175 of 334 PyTorch Jobs in England

inference, and time-series analysis An excellent proficiency of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch) Demonstrable experience enabling impactful change with AI within a financial services institution. Coupling that with prior experience in consulting would be a bonus. You possess proven experience leading data science More ❯

and we actively support that growth. • Experience shipping real products to customers • ML Design and Deployment: Familiarity with designing, training, optimizing, and deploying machine learning models using frameworks like PyTorch, JAX, LiteRT, HuggingFace Transformers, or commercial APIs. • Containerisation: Experience with cloud deployments and containerisation (Docker, Kubernetes, containerd). • Linux: Embedded Linux and kernel development. • Programming Languages: We adopt a flexible 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 ❯

implementing AI solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React More ❯

Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯

computing, monitoring and operational data analytics, mathematical optimisation, containers, compilers, or application optimisation. You Should Have A good working knowledge of AI/ML frameworks, at least TensorFlow and PyTorch, as well as the data preparation, handling, and lineage control, as well as model deployment, in particular in a distributed environment. At least a B.Sc. equivalent in a Science, Technology More ❯

Kernel, AI Foundry, or similar. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/tools such as PyTorch and TensorFlow. Core Skills and Qualifications: 6+ years of experience in software engineering, with at least 2 years focused on building or integrating AI/ML solutions. Hands-on experience More ❯

and/or Semantic Kernel. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/tools such as PyTorch and TensorFlow. Core Skills and Qualifications: 8+ years of professional software engineering experience, including 3+ years working directly on AI/ML systems or platforms. Hands-on experience with Microsoft More ❯

translate business needs into technical solutions. Requirements At least 3 years of experience in applied machine learning and deploying production models. Proficiency in Python, SQL, and frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with AWS services and Databricks; understanding of ML Ops is highly beneficial. Ability to adapt quickly to new tools and deliver scalable solutions independently. Familiarity with More ❯

containerisation tools Experience working with APIs for data extraction Desirable Skills Familiarity with big data technologies such as Spark and Kafka Experience with machine learning frameworks like TensorFlow or PyTorch Knowledge of data visualisation tools such as Power BI or Tableau Strong understanding of data modelling and database optimisation Experience with dimensional data modelling Interested in learning more? Apply now More ❯

on experience in both machine learning engineering (training ML models), and who have full-stack SWE experience - both backend and frontend engineering. Ideal candidates should have experience with Python, Pytorch, JS and React and similar frameworks. Responsibilities: Carry out software development and research for designing automated LLM agents for coding, ML engineering and research tasks, including building agent analysis tools More ❯

on experience in both machine learning engineering (training ML models), and who have full-stack SWE experience - both backend and frontend engineering. Ideal candidates should have experience with Python, Pytorch, JS and React and similar frameworks. Responsibilities: Carry out software development and research for designing automated LLM agents for coding, ML engineering and research tasks, including building agent analysis tools 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 ❯

a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI More ❯

a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI More ❯

cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus 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 ❯

to model deployment , Experience with some of the following tools and technologies (or an eagerness to learn): , Python and its data science ecosystem (e.g., pandas, scikit-learn, TensorFlow/PyTorch) , Statistical methods and machine learning (e.g., A/B testing, model validation) , Data pipelining tools like SQL, dbt, BigQuery, or Spark , A strong communicator with the ability to communicate technical More ❯

ended problems. (Desirable) Experience designing and conducting experiments in a social science or human-computer interaction (HCI) context. Strong proficiency in Python and common ML libraries/frameworks (e.g., PyTorch, JAX, TensorFlow, Hugging Face). (Desirable) A track record of publications in relevant AI or interdisciplinary conferences. A strong scientific mindset geared towards rigorous experimentation, coupled with the engineering discipline More ❯

practices Experience in CI/CD (e.g. CircleCI). Preferred Qualifications Familiarity and enthusiasm about AI-based coding solutions (e.g. Cursor, Windsurf, etc.) Familiarity with ML concepts and frameworks (PyTorch). Experience in large-scale processing of multimodal computer vision data (images, videos, captioning, etc) for ML purposes. Experience in Structure-from-Motion for large-scale 3D reconstruction of image More ❯

in LLMs and Algorithms Experience with data preprocessing and feature extraction Proficiency in programming languages like Python or R (4+ years) Knowledge of machine learning frameworks like TensorFlow or PyTorch Excellent problem-solving and analytical skills What you don't know, we can teach - as long as you have the desire to learn. We are a group of serious engineers More ❯

time ML applications Maintain and improve recommender systems Build and work with modern API and microservices architectures Qualifications Strong foundation in Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD More ❯

and propose optimizations. Essential Proven experience as a Machine Learning Engineer with at least 3 years of professional experience. Strong proficiency in machine learning frameworks such as CatBoost , TensorFlow , PyTorch , or Keras . Experience with image processing , feature extraction , and text preprocessing techniques . Solid understanding of algorithms for tasks such as object detection , image classification , text extraction , and sentiment More ❯

state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX. Managing and processing large-scale datasets and implementing advanced data augmentation strategies. More ❯