1 to 25 of 807 PyTorch Jobs

quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit‐Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. ...

quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. ...

quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. ...

responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

bring experience in managing, coaching and developing junior members of a team and wider community. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems, building ...

Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

sized for training and checkpointing workloads. AI Software, MLOps & Generative AIOrchestration & containers: Kubernetes, Docker, Slurm, Run:ai or equivalent GPU scheduling platforms. ML frameworks: PyTorch and TensorFlow at a working, hands-on level. Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM ...

Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud services such as AWS, GCP, and Azure Experience with AI modeling frameworks such as TensorFlow, PyTorch, Keras, or Scikit-Learn, and familiarity with AI Governance and Safety principles, including Responsible AI practices, bias and hallucination testing, and LLM safety guardrails Experience ...

pipelines and models for scalability, cost-efficiency, and performance at scale. Leverage modern data stack technologies including SQL, Python (Pandas, Scikit-learn, TensorFlow/PyTorch), Spark, Databricks, and cloud platforms. Maintain clear documentation of data pipelines, models, and processes. Mentor junior team members and promote best practices. Stay ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

engineering and building integrated solutions Strong articulation, stakeholder management and consulting skills Experience driving productivity and cost optimisationsSkills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain,Langsmith/Langfuse, Gen AI/Agentic AI , Cloud platforms (Azure AI Foundry, AWS Bedrock/Sagemaker, GCP Vertex ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

implement models, optimize performance, and manage training pipelines effectively. Technical Proficiency: Proficiency in programming languages commonly used in AI development, such as Python, TensorFlow, PyTorch, or similar tools, along with modern LLM/agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon ...

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 ...

innovation. ESSENTIAL SKILLS & EXPERIENCE: Strong Python development experience within commercial or industrial environments. Experience developing AI and Machine Learning solutions using frameworks such as PyTorch, TensorFlow or Scikit-Learn. Knowledge of autonomy frameworks such as ROS2 or equivalent technologies. Experience working with Computer Vision, Deep Learning, NLP/ ...

supervised and unsupervised learning, time series forecasting, clustering, optimization, geospatial modeling, and generative AI; familiarity with libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, Hugging Face Transformers, and pandasSolid engineering capabilities in Python and JavaScript, with hands-on experience building and operationalizing solutions using FastAPI and ReactComfortable working with ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). Benefits Package and Benefits: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). What We Offer: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training ...

GitHub, Docker/Kubernetes, MLflow, Jira. Edge deployments: Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators. Distributed model training & infra: Pytorch DDP, FDSP and TorchTitan, Megatron, Slurm, Run:ai, DeepSpeed, Kubernetes, cloud or on-prem GPU clusters. About you You’ve built ML systems that persist—deployed ...