51 to 75 of 341 TensorFlow Jobs in England

For Education & Experience – Strong academic background in Data Science, Machine Learning, AI, or a related field. Technical Skills – Proficiency in Python, SQL, ML frameworks (TensorFlow, PyTorch, scikit-learn), and at least one OOP language (Rust, C++, C#). AI & NLP Expertise – Hands-on experience with LLMs, NLP, and AI More ❯

For Education & Experience – Strong academic background in Data Science, Machine Learning, AI, or a related field. Technical Skills – Proficiency in Python, SQL, ML frameworks (TensorFlow, PyTorch, scikit-learn), and at least one OOP language (Rust, C++, C#). AI & NLP Expertise – Hands-on experience with LLMs, NLP, and AI More ❯

in machine learning/NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning More ❯

in machine learning/NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning More ❯

models. - Experience communicating across technical and non-technical audiences. - Experience in using Python and hands-on experience building models with deep learning frameworks like TensorFlow, Keras, PyTorch, MXNet. - Fluency in written and spoken English. PREFERRED QUALIFICATIONS - Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue). - PhD More ❯

ICML, EMNLP, CVPR, etc.) and/or journals Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc. Strong written and verbal communication skills to operate in a cross functional team environment More ❯

or related field research - Experience programming in Java, C++, Python or related language - 3+ years' experience with modeling languages and tools like PyTorch/TensorFlow, R, scikit-learn, numpy, scipy, etc - Solid ML background and familiar with standard NLU, NLG, and LLM techniques PREFERRED QUALIFICATIONS - PhD in Computer Sciences More ❯

frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g., OpenLink More ❯

frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g., OpenLink More ❯

Able to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure More ❯

. Stay up-to-date with the latest research and advancements in AI, Image processing, and Computer Vision. Familiarity with deep learning frameworks (PyTorch, TensorFlow) including OpenCV. Strong communication and analytical skills. Ability to work in teams in a diverse, multi-stakeholder environment comprising of Business and Technology teams. More ❯

CI/CD pipelines, monitoring frameworks). Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus Cloud experience—AWS preferred - including deploying and managing models in cloud environments (will still consider GCP/Azure) Curious More ❯

data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions More ❯

practical experience). 2-3 years of experience in machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and More ❯

strengths and interests, you may be asked to work outside your job description. Our tech stack Languages: Python (PyTorch, NumPy, OpenCV) ML Frameworks: PyTorch, TensorFlow, OpenCV Infrastructure: AWS, GCP, Docker, Kubernetes, MLFlow MLOps Tools: DVC, Weights & Biases, TensorRT Version Control & CI/CD: GitHub, GitLab, Jenkins Key Responsibilities Develop More ❯

timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques More ❯

ideal candidate has a strong background in software development best practices, mathematics, and statistics, as well as experience with machine learning frameworks such as TensorFlow or PyTorch. Candidates should also have excellent programming skills in Python and be familiar with data processing and analysis tools. Candidates should be able More ❯

a plus. Hands-on experience with Google Cloud AI tools, such as Vision AI, Speech-to-Text, or AutoML. Proficiency in ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Expertise in container orchestration for AI workloads using Google Kubernetes Engine (GKE) or Kubernetes. Background in software engineering, data science More ❯

a plus. Hands-on experience with Google Cloud AI tools, such as Vision AI, Speech-to-Text, or AutoML. Proficiency in ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Expertise in container orchestration for AI workloads using Google Kubernetes Engine (GKE) or Kubernetes. Background in software engineering, data science More ❯

in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR). Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ) Experience in ML Research beyond completing a PhD (e.g. supervision, industry experience, leading academic initiatives, ). Excellent communication skills to report and present research More ❯

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 More ❯

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 More ❯

understanding of object-oriented programming concepts. Experience in designing and implementing ETL pipelines, data warehousing, and data modeling. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Expertise in statistical modeling, machine learning algorithms, and data mining techniques. Familiarity with data visualization and reporting tools, such as More ❯

industry experience, or an MS with significant industry or research experience in the field. Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas). Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model More ❯

and pipeline development. Deep understanding of data modelling, data access, and data storage techniques. Familiarity with machine learning frameworks and data visualization tools (e.g., TensorFlow, Scikit-learn, Tableau, Power BI). Exceptional problem-solving skills and the ability to lead a team under tight deadlines. Excellent communication skills for More ❯