1 to 25 of 291 TensorFlow Jobs

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 ...

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 ...

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 ...

clean, efficient, and maintainable code to enable scalable and production-grade AI/ML solutions. Extensive experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), with the ability to design, implement, and optimise scalable solutions while guiding teams in the effective use of these tools. Extensive expertise ...

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. ...

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 ...

production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts and tooling ...

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 ...

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 Experience ...

bring5+ years of experience in AI, Machine Learning, Data Science, or related fields.Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, and Hugging Face.Experience taking AI proof-of-concepts from idea to production.Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine-tuning LLMs ...

Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing ...

collecting technology keywords. Useful experience Experience with some of the following would be valuable, but we do not expect you to know everything: PyTorch, TensorFlow or JAX Hugging Face LLM APIs and open-source models RAG and vector databases Apache Airflow AWS S3 ECS/EKS Redshift Docker Kubernetes ...

Community of Practice. Experience Required Essential Strong Python programming and hands-on experience with core ML/AI libraries (for example scikit-learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience deploying AI/ML in the cloud, particularly Microsoft Azure ...

services environment. In-depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation ...

services environment. In-depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation ...

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 skillsPreferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps ...

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 ...

leadership across the team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow ...

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 ...

would be highly beneficial: Machine Learning and AI Engineering Generative AI and Large Language Models Prompt engineering and context engineering scikit-learn, PyTorch or TensorFlow LangChain or similar AI frameworks Cloud data platforms and services across AWS, Azure or GCP Data warehouses and modern data platforms Big data ...

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 ...

junior members of a team and wider community. Must have active UK Government Security ClearanceDESIRABLE: 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,coachingand 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 ...