51 to 75 of 549 PyTorch Jobs in England

monitoring with open telemetry and open inference. Knowledge of observability stacks, open Bonus Points Experience with AI and machine learning frameworks at scale (e.g., PyTorch, DeepSpeed, Megatron-LM, vLLM). Hands-on experience with major cloud platforms (e.g., AWS, GCP, Azure) and hybrid cloud architectures. Advanced experience with containerization (Docker ...

dimensional datasets, ensuring efficient data loading and manipulation within training pipelines, and overseeing data quality and storage optimisation. Familiarity with deep learning frameworks (e.g., PyTorch). Architecting and building an ML platform and core ML infrastructure from the ground up, ideally in a biomedical, healthcare or scientific computing domain, including ...

connect operational bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models. Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn. Proficiency in Python with a strong emphasis on code quality and reliability through comprehensive testing. Extensive experience with generative ...

communication skills. Desirable Experience Machine Learning model development and training. LLMs, transformers, RAG and Agentic AI. LangChain, LangGraph or similar AI orchestration frameworks. PyTorch, TensorFlow, Scikit-learn or Hugging Face. Vector databases, embeddings and model evaluation. NLP, Computer Vision or multimodal AI. Edge AI, AI safety, security or explainability. Experience ...

experience training, deploying, and maintaining machine learning models in production Proficiency in Python and relevant AI/ML libraries (such as scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

training, workshops, mentoring or team enablement Awareness of data governance, ethics and responsible AI Eligibility for Enhanced DBS and BPSS clearance Desirable: Experience with PyTorch, TensorFlow, LangGraph, R or Java Experience with Spark, Databricks or similar distributed data platforms, and exposure to MLOps Experience of AWS, Azure ...

statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge of SQL and version control tools ...

developing technical teams. Strong client-facing communication skills, with the ability to engage senior stakeholders and lead technical discussions. Desirable Experience Experience with PyTorch, TensorFlow or other machine learning frameworks. Knowledge of LLM fine-tuning, model distillation and optimisation techniques. Experience with vector databases, semantic search, knowledge graphs or related ...

including orchestration frameworks, context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research ...

security, and compliance. Lead technical reviews and provide guidance on complex AI engineering challenges. Technical Expertise: Deep expertise in AI/ML frameworks—TensorFlow, PyTorch, Scikit‐Learn, Transformers—cloud platforms (AWS, Azure, GCP), and modern software engineering practices. Strong background in deep learning, natural language processing, computer vision, or reinforcement ...

Experience in data and system engineering for large-scale model workflows Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch) Fluent with at least one of the following tools: Cursor, Windsurf, Trae, Gemini CLI, Claude Code, or Codex (or similar) Experience in applying, fine‐tune ...

projects end-to-end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classic ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering. Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine‐tuning. Cloud & MLOps: Production deployment ...

equivalent professional experience Preferred Skills and Experience Familiarity with observability instrumentation for AI systems (OpenTelemetry, Prometheus) Experience with AI/ML frameworks (TensorFlow, PyTorch) and the Hugging Face/open‐source AI ecosystem Experience with image understanding and OCR Working knowledge of policy‐as‐code (OPA/Rego ...

fine-tunethosemodels eg. XGBoost, Deep Neural Networks, Transformers, ResNets,VAEs, GANs,Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementingnew techniques in the field of machine learning as they emerge. Experience ...

Ability to work with non-specialists in a partnership model, conveying information clearly and creating trust with stakeholders. Experience with machine learning frameworks (e.g., PyTorch, TensorFlow), data science packages (e.g., Scikit-Learn, NumPy, SciPy, Pandas, statsmodels) and GenAI toolkit Experience in ML Ops #J-18808-Ljbffr ...

pipelines with an orchestration tool such as Dagster (or Airflow, Prefect, etc.). Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM. Clear evidence of practical experience defining and deploying containerised systems, i.e.: Implementing APIs for internal ...

systems. Strong proficiency in programming languages such as Python, Java, or C++. In-depth understanding of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and NLP techniques. Experience with agent-based modeling, reinforcement learning, multi-agent systems, or cognitive architectures. Solid understanding of software engineering principles, including design patterns ...

/or C/C++ is a strong plus Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux environment with attention to performance ...

point in time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python; data science/statistics, signal research, backtesting or factor modelling ...

system integrations — with a strong focus on GenAI, NLP, computer vision, and multimodal AI applications. Leverage deep knowledge of AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and enterprise architecture best practices (e.g., microservices, APIs, cloud‐native design). AI & Data Platform Architecture/Deployment: Architect robust, secure ...

Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with ...

simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker ...

with video, audio, TV, or edge‐device environments, especially where latency, cost, and hardware constraints matter. Familiarity with ML/DL frameworks such as PyTorch or TensorFlow. Research experience, paper implementation experience, or a habit of applying emerging GenAI techniques pragmatically to real problems. What's Roku's approach ...