24 of 24 PyTorch Jobs in Manchester

used for AI/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

Python, R), with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

similar programming languages used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation ...

/ML and Generative AI solutions; evidence of real-world impact highly desirable.Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred.Deep understanding ...

programming skills in Python, SQL, and/or similar languages.AI/ML Frameworks: Proven experience with popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn. Familiarity with Generative AI and/or machine learning frameworks (e.g., Langchain) is desirable.ML Algorithms: Strong understanding of machine learning algorithms, deep learning ...

research and evaluate applicability to client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics ...

following areas would be highly beneficial: Machine Learning and AI Engineering Generative AI and Large Language Models Prompt engineering and context engineering scikit-learn, PyTorch or TensorFlow LangChain or similar AI frameworks Cloud data platforms and services across AWS, Azure or GCP Data warehouses and modern data platforms Big data ...

them:Applying AI/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.Using cloud-based data science and machine learning services across AWS, Azure, GCP or equivalent platforms.Developing high-quality, maintainable code ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied ...

need...Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs ...

years of experience in data science or applied machine learning, preferably in infrastructure, environmental, or urban development sectors.Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL, with experience in geospatial and environmental data analysis.Experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure ...

languagesExperience building data pipelines and working with structured and unstructured data.Familiarity with Generative AI and/or machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch, Langchain) is desirable. Experience with cloud data platforms, data warehouses, or big data technologies is an advantage. Strong analytical and problem-solving skills, with attention ...

manage AI/RAG/GenAI risk and fine-tune models on proprietary datasets. Strong Python and SQL skills, with frameworks such as PyTorch and TensorFlow. If you're ready to shape AI strategy from the ground up and see it through to production, at real scale, this ...

wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied ...

some of the following areas would be highly beneficial:Machine Learning and AI EngineeringGenerative AI and Large Language ModelsPrompt engineering and context engineeringscikit-learn, PyTorch or TensorFlowLangChain or similar AI frameworksCloud data platforms and services across AWS, Azure or GCPData warehouses and modern data platformsBig data and distributed processing technologiesData ...

integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.)Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow;3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript. Experience working ...

building data pipelines and working with both structured and unstructured dataKnowledge of AI, machine learning or generative AI technologiesExposure to frameworks such as TensorFlow, PyTorch, LangChain or similarExperience working with cloud based data platforms and modern data architecturesStrong analytical and problem-solving skillsExcellent communication skills with the ability to engage ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. Experience ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies.Experience operating in complex ...

practices Skills & Experience * Strong experience with AI engineering, or software engineering (e.g. Python, Java, JavaScript/TypeScript etc.) with libraries/frameworks such as PyTorch, TensorFlow etc.) * Experience with RAG and LLM-based solutions * Solid understanding of AI architectures and data pipelines * Knowledge of security, compliance, and governance principles from ...

leading the design, development, and deployment of sophisticated predictive models. Expertise in Python/R and ML frameworks, such as scikit-learn, TensorFlow, or PyTorch, Proven ability to design and implement complex machine learning solutions and guiding best practice. Deep understanding of statistical analysis and probability theory. Demonstrable experience overseeing ...

Experience with GPU scaling for large-scale machine learning models. Expertise in deploying complex machine learning pipelines in production environments. Desirable Skills: Proficiency with PyTorch and Hugging Face transformers. Experience with neural audio codecs (e.g., Encodec). Background in Text-to-Speech (TTS) development. Experience with advanced techniques such ...

requirement, helpful experience includes: An interest in working with data at scale using tools like dbt, Spark, and AI/ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)Experience with Kafka or other event-driven architectures. During our application process, you will be asked two questions to help us learn more ...