126 to 150 of 1,576 PyTorch Jobs in England

experience). 2-3 years of experience in machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with More ❯

methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in taking advanced statistical/ML solutions from prototype to production and delivering high-impact outcomes to complex business problems Proactive More ❯

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 More ❯

An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example More ❯

or setting up and scaling MLOps platforms in global organizations. Technical Expertise: Strong understanding of AI/ML technologies, algorithms, and frameworks (e.g., TensorFlow, PyTorch, ONNX), as well as experience with AI/ML workload optimization and deployment.Deep expertise in data architecture and engineering principles, data modelling, ETL processes, data More ❯

of AI/ML concepts applied to Digital Twin, with extensive hands-on experience in training and fine-tuning models using frameworks such as PyTorch or TensorFlow Proficiency with Generative AI tools such as GPT, DALL-E, Gemini, and a solid understanding of underlying Machine Learning pipelines Exceptional analytical and More ❯

data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. More ❯

of AI/ML concepts applied to Digital Twin, with extensive hands-on experience in training and fine-tuning models using frameworks such as PyTorch or TensorFlow Proficiency with Generative AI tools such as GPT, DALL-E, Gemini, and a solid understanding of underlying Machine Learning pipelines Exceptional analytical and More ❯

internal best practices and the technical growth of the team. Required Qualifications Proficiency in Python and experience with machine learning libraries (e.g. scikit-learn, PyTorch, TensorFlow), Proven ability to deliver data science projects with measurable outcomes, Strong grounding in statistics, modelling, or applied mathematics, Experience with real-world data: cleaning More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

testing large language model behaviour, prompting and building products with language models. Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, etc). Deep understanding of agentic AI concepts and frameworks (e.g., agentic design patterns, multi-agent systems, reinforcement learning) and their applications in More ❯

Java and Python, and strong understanding of data structures, algorithms, and software design patterns. Experience with AI and Gen AI frameworks (e.g., TensorFlow or PyTorch). Experience with at least one cloud-based platform (e.g., AWS SageMaker or Azure Machine Learning). Adept at translating business problems into solution statements. More ❯

internal best practices and the technical growth of the team. Required Qualifications Proficiency in Python and experience with machine learning libraries (e.g. scikit-learn, PyTorch, TensorFlow), Proven ability to deliver data science projects with measurable outcomes, Strong grounding in statistics, modelling, or applied mathematics, Experience with real-world data: cleaning More ❯

an industry expert in ML model development, deployment, and MLOps at scale. You are deeply comfortable with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch) and have experience working in a microservices architecture (Go Lang experience is a plus). You have extensive experience with real-time ML applications, reinforcement More ❯

scale cloud-native Machine Learning platform Extensive experience with programming languages such as Python, Java, Scala etc. Solid experience with ML frameworks such as Pytorch and Huggingface The ability to work in a team, collaborate with others to solve interesting problems that directly affect our customers Demonstrated critical thinking and More ❯

or Java, and their associated security considerations. Coding experience with AI & ML, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn. Personal Attributes Drive and lead continuous improvement with energy and passion Displays high levels of self-awareness and emotional intelligence in More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

data science - Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools More ❯

data science - Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools More ❯

Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data More ❯