1 to 25 of 579 Permanent TensorFlow Jobs

guardrails, and AI 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 ...

guardrails, and AI 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 ...

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 ...

e.g., 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 ...

e.g., 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 ...

e.g., 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 ...

e.g., 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 ...

e.g., 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 ...

e.g., 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 ...

principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. 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 ...

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 ...

Understanding of responsible AI principles, modelinterpretability,and ethical considerations. Strong interpersonal skillsand team working. 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 ...

Understanding of responsible AI principles, modelinterpretability,and ethical considerations. Strong interpersonal skillsand team working. 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 ...

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 ...

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 ...

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 ...

/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 AI considerations. ...

/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 AI considerations. ...

/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 AI considerations. ...

/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 AI considerations. ...

/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 AI considerations. ...

/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 AI considerations. ...

bias/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization ...

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. ...

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, TensorRT ...