126 to 150 of 280 TensorFlow Jobs in England

both the technical direction and the AI strategy. Expect to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/ More ❯

both the technical direction and the AI strategy. Expect to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/ More ❯

both the technical direction and the AI strategy. Expect to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/ More ❯

both the technical direction and the AI strategy. Expect to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/ More ❯

route53 & s3) Experience with software development life cycle (sdlc) and agile/iterative methodologies Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your More ❯

and product teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client More ❯

and product teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client More ❯

in Data Science. Demonstrated experience in technical consulting, ideally with exposure to public sector. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow). Broad, practical understanding of machine learning and AI methodologies. Proven success in proof-of-concept design and delivery. Strong technical leadership and mentoring skills. Excellent communication and stakeholder More ❯

in Data Science. Demonstrated experience in technical consulting, ideally with exposure to public sector. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow). Broad, practical understanding of machine learning and AI methodologies. Proven success in proof-of-concept design and delivery. Strong technical leadership and mentoring skills. Excellent communication and stakeholder More ❯

Data Scientist/Data Engineer A understand of Palantir would be a huge + Experience of completing projects to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL More ❯

Data Scientist/Data Engineer A understand of Palantir would be a huge + Experience of completing projects to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL More ❯

in this space. The role The role is building AI applications based on LLM and models such as GPT and BERT You'll make use of Python programming, Pyspark, tensorflow, HuggingFace, LangChain, RAG techniques, interfacing with diverse data sets. Cloud data platforms and a diverse set of tools for AI app deployment. The opportunity Work at the forefront of More ❯

Engineer based near Birmingham should have most of the following key skills: - Demonstrated experience delivering business impact and growth through ML solution design and development - Proven experience in Python, TensorFlow/PyTorch, and modern ML frameworks. - Strong background in data modelling, feature engineering, and model deployment. - Experience with SQL, cloud platforms (AWS/GCP/Azure), and API integration. More ❯

Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT More ❯

Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT More ❯

training, evaluating, and deploying state-of-the-art computer vision models (e.g., YOLO, Vision Transformers, Eva) Strong Python skills and familiarity with libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch Experience with ML workflows, MLOps, and best practices in model validation and evaluation Solid understanding of evaluation metrics such as Accuracy, Recall, F1, IoU Highly Desirable Experience More ❯

training, evaluating, and deploying state-of-the-art computer vision models (e.g., YOLO, Vision Transformers, Eva) Strong Python skills and familiarity with libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch Experience with ML workflows, MLOps, and best practices in model validation and evaluation Solid understanding of evaluation metrics such as Accuracy, Recall, F1, IoU Highly Desirable Experience More ❯

quantitative academic background. • Strong Python programming skills and experience with data science libraries (e.g. NumPy, Pandas, Scikit-Learn). • Familiarity with at least one deep learning framework (e.g. PyTorch, TensorFlow). • Excellent grasp of core statistical and machine learning methods. • Ability to communicate technical concepts clearly to stakeholders and clients. • Proven leadership skills within delivery-focused teams. Desirable Experience More ❯

the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/ More ❯

the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/ More ❯

Learning, Computational Biology, Bioinformatics, or related discipline (or equivalent industry experience) Demonstrated ability to apply ML methods to biological or genomic data Strong Python skills with experience in PyTorch, TensorFlow, or scikit-learn Understanding of bioinformatics workflows (e.g. genome assembly, QC, annotation) Experience working with large or complex genomic datasets Familiarity with model evaluation, benchmarking, and explainability Ability to More ❯

Learning, Computational Biology, Bioinformatics, or related discipline (or equivalent industry experience) Demonstrated ability to apply ML methods to biological or genomic data Strong Python skills with experience in PyTorch, TensorFlow, or scikit-learn Understanding of bioinformatics workflows (e.g. genome assembly, QC, annotation) Experience working with large or complex genomic datasets Familiarity with model evaluation, benchmarking, and explainability Ability to More ❯

field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural to you You More ❯

evidenced by publications and preprints. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯