26 to 50 of 149 PyTorch Jobs in the UK

data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages such as NumPy and Pandas. Knowledge of natural language processing techniques and API integration patterns for ML services. Experience delivering projects ...

Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version ...

data scientist (or similar role). Expert proficiency of Python and experience using SQL, alongside using common ML/AI packages (TensorFlow, PyTorch, XGBoost, etc.). Familiarity with statistical (e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing and creating neural network ...

/ML engineering or architecture roles Proven experience in the healthcare or life sciences domain Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) Experience with healthcare data standards (e.g., HL7, FHIR) Familiarity with cloud platforms (AWS, Azure, or GCP) Understanding of data privacy, security, and regulatory requirements in healthcare ...

deliver features Skills & Experience: Strong Python and SQL skills Familiarity with Azure or AWS Some exposure to ML frameworks (e.g. scikit-learn, TensorFlow, or PyTorch) Background in data engineering, analytics engineering, or similar Desirables: ETL/ELT pipeline experience Microsoft Fabric/Data Lake knowledge BI tools (e.g. Power ...

model deployment pipelines (including edge inference) Improve CI/CD workflows for ML systems and automate infrastructure Key Requirements: Strong Python and experience with PyTorch-based training pipelines Experience with distributed training (DDP, FSDP, DeepSpeed) Solid cloud experience (GCP/AWS/Azure) Hands-on with Docker and infrastructure ...

tower neural networks, embedding techniques, and ranking models. 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. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross ...

reviews, and testing strategies. Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build ...

Backend: Node.js, Python, REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack ...

control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models in a production environment. Proven ability ...

following technologies: Java, Python, Data engineering, Data and Database engineering, Agentic AI, Gen AI, Machine Leaning, Generative AI, Scripting, Spark, Hadoop, SQL, NoSQL, PyTorch and one of the cloud technologies like AWS, Azure or GCP. Should have worked in at least two or more industry domains. Should have a good ...

audio, image, or video data Familiarity with cloud platforms (AWS, Azure, GCP) Strong Python skills and experience with ML libraries and frameworks (e.g. TensorFlow, PyTorch) Knowledge of statistics and probability Experience with ML lifecycle tools (e.g. MLflow, Kubeflow, Argo) Understanding of Ethical and Responsible AI principles Security Requirements You must ...

stakeholders Effective problem-solver who takes initiative in complex production settings Experience with scientific computing, deep learning, big data, or health IT ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines, and MLOps tools (desirable) Passion ...

predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases. · Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow). · Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem. · Mathematical Foundation: Strong understanding of probability, time-series analysis ...

Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn. Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations (calculus and linear algebra highly advantageous). Experience working across the full data ...

tooling stack What They’re Looking For 4+ years experience in machine learning, data science, or AI engineering Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow) Experience working with biological or biomedical data (industry or academia) Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, etc.) Familiarity with ...

distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker ...

distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing ...

Strong commercial acumen with a history of influencing the commercial success of AI products and solutions. Desirable Experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow), fine tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g., scikit-learn, XGBoost). Experience with data storage ...

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 Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility Must ...

ICLR. Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets. Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.). Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain. Why Apply Compensation and total rewards ...

understanding of system design: orchestration, memory, deployment, monitoring – Exposure to tools such as LangGraph, ReAct, CoT — or building similar systems from scratch – Familiar with PyTorch/TensorFlow, RAG architectures, vector databases, modern cloud infra – Experience in startup or consulting environments is a plus – Comfortable working autonomously in fast-moving, sometimes ...

ownership of complex problems Strong communication skills, with the ability to explain technical concepts clearly Technical Environment Python (e.g. pandas, scikit-learn, TensorFlow/PyTorch where relevant) SQL and large-scale data processing Cloud-based environments (e.g. AWS, Azure, or similar) Experience with model deployment, monitoring, and lifecycle management ...

Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings ...