1 to 25 of 46 Remote PyTorch Jobs in England

lifecycle. Expertise taking projects from ideation or experimental Jupyter notebooks to full production deployment. Strong programming skills in Python, with familiarity in ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps practices including model drift detection, decay, A/B testing, integration testing, differential testing, Python package building, and code version control. Skilled in data More ❯

Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience). Technical Skills: Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch). Strong understanding of NLP techniques, including tokenization, embeddings, transformers, and attention mechanisms. Experience in retraining and fine-tuning LLMs using large-scale datasets. Familiarity with cloud platforms like AWS More ❯

following): The wider Python (3) data science stack and ecosystem (such as Pandas, NumPy, Jupyter notebooks, SciPy, FastAPI, Flask, Matplotlib, and similar) Core ML and DL frameworks (such as PyTorch (strongly preferred), Keras, TensorFlow, scikit-learn, and similar) Cloud compute, infrastructure, services, and deployment w.r.t. end-to-end data science (ideally AWS (such as S3, EC2, Lambda, ECR, ECS)) Data More ❯

familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed More ❯

familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed More ❯

modelling, or personalization/recommendation. Familiarity with state-of-the-art practice in these domains Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Solid More ❯

AI/ML engineering role, with a demonstrable track record of building and shipping complex systems. Expert-level proficiency in Python and its core AI/ML libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex), and comfortable transitioning to a 'pilot' role using AI tools to amplify your productivity. Proven experience designing, deploying, and managing scalable AI solutions on at least one More ❯

Deep understanding of machine learning algorithms, optimization, architectures, and evaluation. Experience with data engineering workflows, including ETL, pipeline design, and feature extraction. Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, and OpenAI/Anthropic APIs. Familiarity with DevOps & tooling (Git, CI/CD, API integration), front-end & visualization (Streamlit, Gradio, React), and cloud environments More ❯

experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and More ❯

experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and More ❯

across domains. Collaborate on research-to-product translation, turning cutting-edge AI safety research into deployable tools. We're Looking For: Experienced AI/ML engineer with strong Python, PyTorch, or TensorFlow skills. Familiarity with LLMs, reinforcement learning, or generative AI. Passion for AI safety, alignment, or ethics. Problem-solver mindset; comfortable building from scratch in a fast-paced startup More ❯

and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ? Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. ? Ability to work cross-functionally with marketing More ❯

shipping AI features or automation products Essential skills: Strong experience with Machine Learning, LLMs, NLP and Data Science Proven track record of building and deploying AI models (Python, TensorFlow, PyTorch, LangChain) Hands-on with cloud platforms (preferably Azure, or AWS, GCP) Good understanding of APIs, microservices, and data pipelines Able to prototype quickly and communicate findings clearly Why this role More ❯

research and technologies. Document AI workflows, models, and system architecture. Skills & Qualifications Proficiency in programming languages such as Python, Java, or C++. Strong understanding of machine learning frameworks (eg, PyTorch (preferred), TensorFlow, Scikit-learn). Experience with data processing tools and cloud platforms (eg, Azure, GCP, AWS). Knowledge of deep learning, NLP, and computer vision techniques, including experience with More ❯

and AI operations. Strong expertise in designing and deploying LLMs in production environments. Experience with multi-agent systems, orchestration, and workflow automation. Proficiency in Python, AI/ML frameworks (PyTorch, TensorFlow, or similar), and cloud platforms (AWS, GCP, Azure). This is a full-time, permanent role, with a flexible hybrid working arrangement: 2 days in the Warwick office and More ❯

models, and collaborating closely with engineering teams to deploy production‐ready solutions. Ideal candidates should be proficient in Python (Jupyter Notebooks), familiar with machine learning frameworks like TensorFlow or PyTorch, and experienced in analyzing large datasets and building predictive models. In addition, you will write, review, and validate prompt‐based questions used to train AI systems. You are a good More ❯

a team Some hands on experience in a commercial environment, working on AI/ML applications Multi cloud exposure (Azure/AWS/GCP) . Some of the following - Pytorch, GPT/BERT, RAG, Apache Airflow, Power Automate, Azure logic apps, RPA/Zapier, HuggingFace, LangChain... Background in Data Science or Software Engineering The values and ethos of this business More ❯

You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/CD for ML More ❯

AI models, preferably within high-performance or real-time environments. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of data analysis, statistical methods, and predictive modelling. Excellent problem-solving skills and attention to detail. Effective communication and collaboration abilities. Preferred Skills (desirable but More ❯

near Birmingham should have most of the following key skills: - Demonstrated experience delivering business impact and growth through ML solution design and development - Proven experience in Python, TensorFlow/PyTorch, and modern ML frameworks. - Strong background in data modelling, feature engineering, and model deployment. - Experience with SQL, cloud platforms (AWS/GCP/Azure), and API integration. - A commercial mindset 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 ❯

etc. Desire to constantly improve and learn inside and outside of expertise PREFERRED EXPERIENCE: Domain-specific experience in statistics, machine learning, or AMO physics Experience with Numpy, Scipy, and Pytorch Experience with image analysis, emphasis on realtime object detection Experience with databases (relational and non-relational) including but not limited to timeseries data, SQL, and ETL processes Experience creating and More ❯

for the number of days you come to the office. Must-Haves Technical expertise. You have hands-on experience in C++, Python, and several of the following areas: Kubernetes, PyTorch, MLOps (automated re-training, drift monitoring) TensorRT, Nvidia DeepStream/Gstreamer, and AWS. A proven track record. You know how to focus on products, delivering impactful AI/ML products More ❯

the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time More ❯

building features which deliver AI capabilities to some of the biggest names in the insurance industry. We are developing a modern real-time ML platform using technologies like FastAPI, PyTorch, Ray, k8s (helm + flux), Terraform, Postgres, Flink on AWS, React & Typescript. We operate a fully Python stack except for frontend and infrastructure code. We are very big fans of More ❯