1 to 25 of 443 Remote Permanent PyTorch Jobs in England

Science, or related field 3+ years' experience in applied R&D or research consultancy (public sector/defence background advantageous) Strong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Expertise in one or more of the following areas: Multi-modal data fusion or time series analysis Uncertainty quantification or probabilistic modelling Active learning, explainable AI, or More ❯

in Computer Science, Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to fast-paced startup environment More ❯

compliance, and security best practices . Prior experience with cloud-based lakehouse implementation . Experience with machine learning (ML) and AI frameworks, particularly within Databricks (e.g., MLflow, AutoML, or PyTorch/TensorFlow). Understanding of AI-driven analytics and predictive modeling to enhance BI solutions. Think you can make a difference? WE ARE your future. More details: Full time, permanent More ❯

from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Experience with LLM application design and deployment. Strong More ❯

from you: Strong understanding of a wide range of ML algorithms Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch) Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Strong software engineering skills, including version control (Git), code More ❯

algorithms and their practical applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data Engineering Skills: Proficiency in developing and maintaining real-time data pipelines for processing large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency More ❯

data preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers, or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation of More ❯

Pandas, TensorFlow, AI Foundry, OpenAI, Scikit-learn etc.). • Solid understanding of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras). • Proven understanding of software engineering principles, data structures, algorithms, and design patterns. • Experience with version control systems (e.g., Git). • Excellent problem-solving and analytical skills. • Strong communication More ❯

CUDA, Triton); cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API More ❯

Description What We're Looking For: We are looking for a passionate Data Scientist specializing in Natural Language Processing (NLP) and Machine Learning (ML) to contribute to Data Enrichment efforts within Meltwater. As a part of this role, you will More ❯

mechanisms Conduct experiments using A/B testing and statistical analysis to validate approaches Document ML systems and provide support for ongoing performance tuning Use tools like Python, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, MLflow, Docker, SQL , and others Requirements Minimum Bachelor's degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine Learning … Engineer or in a similar role (minimum 1 year ) Strong proficiency in Python and popular ML frameworks (e.g., TensorFlow, PyTorch) Experience deploying machine learning models into production environments Solid understanding of data structures , algorithms , and statistical learning Familiarity with cloud platforms (AWS, Azure, or GCP) and ML pipeline orchestration Bonus: Experience with deep learning , NLP , recommendation systems , or computer vision 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 ❯

Python and strong knowledge of ML algorithms—ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch, with a focus on optimizing performance and scalability for realworld applications. Demonstrated ability to mentor and lead technical teams, influence technical strategy, and drive innovation in fast-paced environments. Expertise More ❯

Lead Machine Learning Engineer, Associate Director, London Join to apply for the Lead Machine Learning Engineer, Associate Director, London role at Fitch Group, Inc. Lead Machine Learning Engineer, Associate Director, London 2 weeks ago Be among the first 25 applicants More ❯

Applied Maths, Computational Linguistics, or related fields (MSc/PhD preferred). Experience with computational linguistics is highly desirable. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, Scikit-learn. Experience deploying AI solutions using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD, and model performance monitoring. Background in behavioural biometrics, human-computer More ❯

. Any candidates with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. More ❯

MSc/PhD preferred). Exposure to computational linguistics is highly desirable, from both academic research and commercial perspectives. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD for ML, and model performance monitoring. More ❯

such as Python or R. Experience with SQL and familiarity with database management practices to handle and query large datasets efficiently. Knowledge of machine learning frameworks like TensorFlow or PyTorch and libraries such as scikit-learn. Proficiency in using data analysis and visualization tools to interpret data and present insights effectively. Proven experience as a Data Scientist, Data Analyst, or More ❯

portfolio of projects involving models like GANs, VAEs, transformers, or diffusion models Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or Keras Strong understanding of deep learning architectures, neural networks, and statistical modeling techniques Experience with cloud platforms (AWS, Azure, Google Cloud) and MLops tools for model deployment and management More ❯

Python and strong knowledge of ML algorithms—ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch, with a focus on optimizing performance and scalability for realworld applications. Demonstrated ability to mentor and lead technical teams, influence technical strategy, and drive innovation in fast-paced environments. Expertise More ❯

Fitch Group is currently seeking a Lead Machine Learning Engineer, Associate Director based out of our London office. As a leading, global financial information services provider, Fitch Group delivers vital credit and risk insights, robust data, and dynamic tools to More ❯

understanding. Machine Learning & Statistical Modelling Implement both classical ML methods (regression, clustering, time-series forecasting) and advanced algorithms (XGBoost, LightGBM). Address computer vision, NLP, and generative tasks using PyTorch, TensorFlow, or Transformer-based models. Model Deployment & MLOps Integrate CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker Pipelines. Monitor model performance over time and … mitigation. Employ model explainability methods (SHAP, LIME) and adopt best practices for responsible AI. Qualifications Technical Skills Programming: Python (NumPy, Pandas), R, SQL. ML/DL Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers. Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI. Automation: MLflow, Kubeflow, Weights & Biases for experiment tracking and deployment. Architectural Competencies Awareness of data More ❯

. Any candidates with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. More ❯

knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks. More ❯

Proven ability to lead technical direction across projects or domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice to have: Experience in setting or influencing data science strategy in a growing organisation Familiarity with AWS SageMaker and More ❯