1 to 25 of 645 PyTorch Jobs

Machine Learning Deep Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow Scikit-learn LangChain Hugging Face OpenAI and Azure OpenAI Services Vector Databases Docker Kubernetes Cloud Platforms Microsoft Azure Azure AI Services Azure Machine Learning ...

levels) Requirements Skills and Qualifications Essential Skills: Strong Python/R (pandas/NumPy; ML libs such as scikit-learn; DL frameworks TensorFlow/PyTorch). Experience with LLM/RAG toolchains (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector search (e.g., Pinecone, Weaviate, FAISS, Azure AI Search). Hands ...

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. ...

experience in managing, coaching and developing junior members of a team and wider community. D ESIRABLE : 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 ...

assistants/agents).Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy).Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures.Practical experience with LLMs, prompt engineering, RAG and tools ...

assistants/agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures. Practical experience with LLMs, prompt engineering ...

assistants/agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures. Practical experience with LLMs, prompt engineering ...

hands‐on experience in AI/ML development. Proven experience delivering AI solutions to production. Strong expertise in Python and frameworks such as PyTorch, TensorFlow, and Scikit-learn. Hands‐on experience with Generative AI, LLMs (such as GPT, Claude, and Llama), and prompt engineering. Strong knowledge of RAG, embeddings ...

programming languages like Python for model development, experimentation, and integration with OpenAI API. Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API. Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices ...

technical demonstrations, bids, proofs of concept and customer workshops. Required Skills Strong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit‐Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time‐series ...

technical demonstrations, bids, proofs of concept and customer workshops. Required Skills Strong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit‐Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time‐series ...

technical demonstrations, bids, proofs of concept and customer workshops. Required Skills Strong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit‐Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time‐series ...

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 ...

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 ...

learning and deep learning, time series forecasting, reinforcement learning, optimization, or conversational AI. Familiarity with Python and common AI/ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn, Pandas, NumPy). Software engineering fundamentals — version control, code review, modular design, and writing testable code intended for someone else ...

areas that require experimentation and rapid problem solving. Preferred : Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn. In-depth knowledge of one or more areas of deep learning, such as natural language generation (LLMs, Sentiment Analysis), recommendation systems ...

code reviews and technical design discussions. Support testing, deployment, and ongoing optimisation activities. Qualifications Strong proficiency in: Python SQL Experience with: Scikit-learn PyTorch and/or TensorFlow Main AI services from leading cloud service and model providers Supervised and unsupervised learning Statistical concepts Generative AI Practical experience 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 ...

agent evaluation frameworks such as Mosaic AI Agent Evaluation, Garak, or bespoke evaluation harnesses. Strong background in advanced machine learning, including deep learning with PyTorch, computer vision methods, NLP pipelines, or graph‐based data processing. Knowledge of cloud infrastructure and modern deployment practices, including Terraform or Bicep, Kubernetes, serverless architectures ...

Experience with Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning or related Azure AI services. AI engineering tools. Familiarity with frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain or LlamaIndex, and with vector databases or semantic search. Full-stack delivery. Exposure to Docker, CI/CD, REST ...

parallel and high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads. AI Software, MLOps & Generative AI 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 ...

engineers to integrate AI into applications Requirements ✓ Degree in Computer Science, Data Science, Mathematics or equivalent experience ✓ Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn) ✓ Experience building and deploying production ML models ✓ Understanding of supervised and unsupervised learning techniques ✓ Experience with cloud platforms (AWS, Azure ...

deploying AI applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...