276 to 300 of 1,231 TensorFlow Jobs in England

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Mathematics, or a related field. Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms. Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java). First author in research publications in peer-reviewed conferences More ❯

if: You have strong foundational software engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g., TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy, and maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality More ❯

a deep understanding of OAuth, JWT/JWE/JWS. Solid understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus. Python engineering experience React #J-18808-Ljbffr More ❯

PhD) in a relevant field 5+ years of hands-on experience in MLOps and Research Engineering Strong proficiency in programming languages such as Python, with experience in libraries like TensorFlow, PyTorch, and scikit-learn Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring Prior commercial experience in designing More ❯

if: You have strong foundational software engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g., TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy, and maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

/PhD in Computer Science, Data Science, Mathematics, or related field. 5+ years of experience in ML modeling, ranking, or recommendation systems . Proficiency in Python, SQL, Spark, PySpark, TensorFlow . Strong knowledge of LLM algorithms and training techniques . Experience deploying models in production environments. Nice to Have: Experience in GenAI/LLMs Familiarity with distributed computing tools More ❯

computing, or data engineering. Work Experience: Proven background in AI/ML, developing and deploying generative AI solutions at scale. Experience with LLMs like GPT and BERT, AI frameworks (TensorFlow, PyTorch), cloud-native solutions, and tools like Databricks and Snowflake. Strong cloud and AI deployment experience. Stakeholder management skills. Skills: Expertise in designing and optimizing generative AI models, prompt More ❯

understanding of key concepts in computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python including Pytorch, Tensorflow and SKLearn as well as initial knowledge of LangChain, RAGAS and CI/CD You can demonstrate a growth mindset in terms of picking up new challenges and transforming More ❯

understanding of key concepts in computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python including Pytorch, Tensorflow and SKLearn as well as initial knowledge of LangChain, RAGAS and CI/CD You can demonstrate a growth mindset in terms of picking up new challenges and transforming More ❯

such as Python, R, C, C++, or Java, and their associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. Strong More ❯

Practical experience in developing and maintaining ML systems with tools such as MLflow, BentoML, and Evidently AI. Exposure to learning methodologies leveraging advanced modeling frameworks such as PyTorch and TensorFlow will be beneficial. Familiarity with data governance and compliance standards. Certification as a Kubernetes Administrator or Developer (CKA/CKAD). Exposure to diverse cloud compute and data processing More ❯

such as Python, R, C, C++, or Java, and their associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. Strong More ❯

or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional More ❯

machine learning - Experience in building machine learning models for business application - Experience in applied research PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD #J-18808-Ljbffr More ❯

Claude, Gemini, Llama, Falcon, Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL More ❯

LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike More ❯