151 to 175 of 737 TensorFlow Jobs in London

processing from heterogeneous sources; familiarity with tools like Apache Spark or Hadoop. Proficiency with cloud platforms (AWS, GCP, Azure). Familiarity with major machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Open-source contributions or publications demonstrating expertise in machine learning for scientific applications. Hands-on experience with best software development practices in collaborative environments. #J-18808-Ljbffr More ❯

in data science or software engineering. 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, for example, supervised/unsupervised More ❯

in data science, with a focus on NLP, Generative AI and LLMs. Proficiency in Python and experience working with LLMs and NLP frameworks (e.g. Hugging Face, Spacy, Pytorch/Tensorflow etc). Experience with Prompt Engineering, RAG techniques and various evaluation methodologies for integrating GenAI with search/retrieval systems and measure the quality. Experience with LangChain/LlamaIndex More ❯

neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow or PyTorch. Experience with cloud platforms such as AWS SageMaker or Azure Machine Learning. Ability to translate business problems into solutions. Strong communication skills; bilingualism/multilingualism is a More ❯

projects that focus on optimization, demonstrating an ability to mentor teams and manage cross-functional projects effectively. Machine Learning Integration: Knowledge in integrating optimization with machine learning techniques (using TensorFlow, PyTorch) to enhance decision-making processes and model performance. Cloud and MLOps for Optimization Models: Familiarity with deploying and managing optimization models on cloud platforms (AWS, GCP, Azure) and 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 About Us J.P. Morgan is More ❯

Required qualifications to be successful in this role • Proven experience in enterprise architecture, projects specifically in AI/ML systems design • Deep understanding of AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and cloud platforms (AWS, Azure, GCP) • Strong experience with data architecture, pipelines and governance (e.g., data lakes, ETL, MLOps) • Knowledge of regulatory and ethical considerations in More ❯

processing from heterogeneous sources; familiarity with tools like Apache Spark or Hadoop. Proficiency with cloud platforms (AWS, GCP, Azure). Familiarity with major machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Open-source contributions or publications demonstrating expertise in machine learning for scientific applications. Hands-on experience with best software development practices in collaborative environments. Seniority level Seniority More ❯

in data science or software engineering. 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, for example, supervised/unsupervised More ❯

processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams with diverse skillsets. Deploying machine learning models and systems to production (DevOps, MLOps, CI/CD). Experience of More ❯

techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using More ❯

tracking progress, sharing ideas, and collaborating. Engaging with partners to meet their requests. Additional skills we value: Azure Machine Learning Services, Cognitive Services, Responsible AI Dashboard Python, SKLearn, XGBoost TensorFlow, PyTorch Model deployment options like Azure Functions, FastAPI, Kubernetes CI/CD pipelines, Git actions Infrastructure as code: Terraform, ARM Templates, Databricks Asset Bundles Advanced ML techniques: Graph processing 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 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce More ❯

a related field (or equivalent 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 familiarity with NLP algorithms and More ❯

a related field (or equivalent 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 familiarity with NLP algorithms and More ❯

a related field (or equivalent 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 familiarity with NLP algorithms and More ❯

a related field (or equivalent 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 familiarity with NLP algorithms and More ❯

in data science or software engineering. 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, for example, supervised/unsupervised More ❯

learning to real world commercial problems Experience bringing live services using machine learning and python to production. Expert knowledge of Python and relevant libraries (numpy, pandas, matplotlib, Scikit-learn, tensorflow, etc...) knowledge in other programming languages is valuable, but this is primarily a Python shop. Experience with things like CI/CD pipelines, Docker or similar, cloud hosting, good More ❯

or deep learning models and solutions. 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 Hebrew and English. Preferred Qualifications Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models. More ❯

or Data Science with reasonable 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 performance aligned with business goals Experience More ❯

programming languages such as Python. Experience with data visualization tools like Power BI. Familiarity with data manipulation libraries such as Pandas and NumPy. Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Excellent problem-solving skills and attention to detail. Ability to work effectively both independently and as part of a team. Strong communication skills, both written More ❯

programming languages such as Python. Experience with data visualization tools like Power BI. Familiarity with data manipulation libraries such as Pandas and NumPy. Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Excellent problem-solving skills and attention to detail. Ability to work effectively both independently and as part of a team. Strong communication skills, both written More ❯

programming languages such as Python. Experience with data visualization tools like Power BI. Familiarity with data manipulation libraries such as Pandas and NumPy. Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Excellent problem-solving skills and attention to detail. Ability to work effectively both independently and as part of a team. Strong communication skills, both written More ❯

traditional machine learning, deep learning and generative AI methods for both supervised, self-supervised and unsupervised learning with an emphasis on vision. Proficiency with deep learning frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable. Ability to communicate complex technical concepts More ❯