1 to 25 of 159 TensorFlow Jobs

experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs, including ...

Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative ...

Language Models, including OpenAI, Anthropic, Cohere, Amazon Bedrock, or similar enterprise AI platforms. Strong proficiency in Python and AI/ML libraries, including PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, and related ML frameworks. Experience building Retrieval-Augmented Generation solutions, including embeddings, vector databases, semantic search, document retrieval, chunking strategies ...

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 ...

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 ...

understanding of ML and deep learning methods and large language models. Extensive experience with ML/DL toolkits and libraries (e.g., Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, scikit-learn, pandas). Demonstrated leadership in proposing and delivering AI/ML and GenAI solutions; ability to drive technical direction ...

strong understanding ofML and deep learning methods and large language models.\ NExtensive experiencewith ML/DL toolkits and libraries (e.G., Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, scikit-learn, pandas).\ NDemonstrated leadership in proposing and delivering AI/ML and GenAI solutions; ability to drive technical direction and influence ...

considerations.\ N\n\n\n\ NStrong interpersonal skills and team working.\ N\n\nDESIRABLE: \ N\n\nDemonstrableexperience 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).\ N\n\n\n\ NExperience ...

coaching, and developing junior members of a team and wider community.\ N\n\nDESIRABLE: \ N\n\nDemonstrableexperience 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).\ N\n\n\n\ NExperience ...

coaching and developing junior members of a team and wider community.\ N\n\nDESIRABLE: \ N\n\nDemonstrableexperience 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).\ N\n\n\n\ NExperience ...

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 ...

large scale production environments.\ N\n\nExperience managing data science teams and couching team members\ N\n\nProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).\ N\n\nHands-onexperience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).\ N\n\nExperience with generative models (transformers, GANs ...

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 ...

Microsoft Azure) \n Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes \n Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries) \n Strong problem-solving and communication skills \n\n Preferred Qualifications \n \n Experience with NLP, computer vision ...

Google Cloud Platform, or Microsoft Azure)Knowledge of containerisation technologies like Docker and orchestration tools such as KubernetesExperience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries)Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with ...

Cloud Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries) Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with ...

LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication and collaboration ...

Python and SQL, with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such ...

Experience with MLOps practices and tools for managing the machine learning lifecycle. \n Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. \n Strong understanding of data preprocessing, feature engineering, and evaluation techniques. \n Experience working with large, complex datasets and applying statistical analysis. ...

large-scale production environments.Experience with MLOps practices and tools for managing the machine learning lifecycle.Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Experience working with large, complex datasets and applying statistical analysis.Familiarity with cloud platforms ...

production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity ...

production environments.\ NExperience with MLOps practices and tools for managing the machine learning lifecycle.\ NProficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.\ NStrong understandingof data preprocessing, feature engineering, and evaluation techniques.\ NExperience working with large, complex datasets and applying statistical analysis.\ NFamiliarity with ...