1 to 25 of 82 TensorFlow Jobs with Hybrid or WFH Options

leading and delivering successful data science projects. Proficiency in programming languages such as Python, R, or Scala. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong knowledge of statistical modelling, data mining, and data visualization techniques. Experience with big data technologies (e.g., Hadoop, Spark) and more »

with a strong focus on machine learning and time series forecasting. Expertise in Python and its data science libraries (e.g., Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch). Solid understanding of ML and data pipeline architectures and best practices. Experience with big data technologies and distributed computing (e.g., Spark, Hadoop more »

and robust data pipelines, models, and applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc.Build and deploy production grade fine-tuned LLMs and RAG architecture.Create and manage the complex and robust prompts across the GenAI solutions.Communicate effectively more »

and robust data pipelines, models, and applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc.Build and deploy production grade fine-tuned LLMs and RAG architecture.Create and manage the complex and robust prompts across the GenAI solutions.Communicate effectively more »

and robust data pipelines, models, and applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc.Build and deploy production grade fine-tuned LLMs and RAG architecture.Create and manage the complex and robust prompts across the GenAI solutions.Communicate effectively more »

and robust data pipelines, models, and applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc.Build and deploy production grade fine-tuned LLMs and RAG architecture.Create and manage the complex and robust prompts across the GenAI solutions.Communicate effectively more »

or a related field. Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn). more »

Linux, Docker, CI/CD. Has a strong opinion on their IDE/editor of choice Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential.Knowledge of MLOps is not essential, but some awareness of this emerging space is more »

database technologies and Semantic Search techniques & tools.Experience in writing robust and efficient code in Python.Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain.Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments.Experience in more »

in PythonStrong NLP experience - NumPy, Pandas etc.Commercial experience leveraging open-source models, finetuning LLMs & RAG pipelinesExpertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch etc.)MLOps experienceNice to have:Familiarity with Git or other Version Control SystemsComputer Vision Library exposureUnderstanding of Big Data Technologies (Hadoop, Spark etc more »

Learning. Familiarity with Azure Databricks desirableSolid background in machine learning algorithms, data preprocessing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable.Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB.Understanding of CI/CD pipelines more »

database technologies and Semantic Search techniques & tools.Experience in writing robust and efficient code in Python.Experience in using tools related to deep learning like PyTorch, TensorFlow, LangChain.Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments.Knowledge in more »

database technologies and Semantic Search techniques & tools.Experience in writing robust and efficient code in Python.Experience in using tools related to deep learning like PyTorch, TensorFlow, LangChain.Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments.Knowledge in more »

statistical skills Experience in software design and development using Python, Pandas and SQL/NoSQL Beneficial knowledge of data science packages, sk-learn, scipy, tensorflow, etc. An understanding of the horse racing industry Quantitative Analyst Sports Trading and Analytics Company Hybrid - 3 days office, 2 days WfH Up to more »

development methodology Familiarity with CI/CD and pipeline automation Familiarity of machine learning principals/pipelines and associated toolsets such as Pytorch and Tensorflow Familiarity with Azure, AWS, GCP products and services - Knowledge of technologies including: Docker or Kubernetes Distributed version control systems such as Git Exposure to more »

in a commercial setting. Programming Skills: Proficiency in programming languages such as Python, C++ , and experience with computer vision libraries and frameworks like OpenCV, TensorFlow, or PyTorch. Algorithm Development : Strong skills in developing and optimising computer vision algorithms for object detection, tracking, segmentation, and classification . Machine Learning : Solid more »

in a commercial setting. Programming Skills: Proficiency in programming languages such as Python, C++ , and experience with computer vision libraries and frameworks like OpenCV, TensorFlow, or PyTorch. Algorithm Development : Strong skills in developing and optimising computer vision algorithms for object detection, tracking, segmentation, and classification . Machine Learning : Solid more »

/AI strategy. Key skills: Python for Machine Learning and Data Science Computer Vision Frameworks used in Machine Learning and Data Science such as TensorFlow, PyTorch, and scikit-learn. Data Science and Visualisation libraries including Pandas, NumPy, scikit-learn, matplotlib, Seaborn. Cloud services used in machine learning and data more »

challenges. Desirable Technical Experience: Proficiency in Java, Kotlin, or Python. Experience with NLP, ML-Ops, and data pipelines. Familiarity with ML frameworks such as TensorFlow or PyTorch Strong understanding of ML algorithms, statistical techniques, and data analysis. Experience with AWS or other cloud technology Background in AI/ML more »

implementing, and deploying machine learning models and algorithms in a production environment. Proficiency in machine learning and deep learning frameworks and libraries such as TensorFlow, PyTorch, or similar. Strong programming skills in Python or another relevant language. Deep understanding of recommender systems, search & ranking algorithms, and marketing analytics. Excellent more »

ecosystem (Lab, Notebook) and related libraries and tooling. Python libraries for data management, statistical analysis, machine learning, and visualisation. Machine learning frameworks such as TensorFlow and PyTorch. Knowledge of Natural Language Processing and Computer Vision applications. Strong understanding of basic probability concepts. In-depth knowledge of the machine learning more »

developing and testing API functionality, JavaScript, C++ and developing for scalability and systems architecture is required. Experience in networking, data management, machine learning, Pytorch, Tensorflow, Keras, and/or Cuda is desirable.Systems Integration Specialist- job responsibilities:Apply existing knowledge and experience of systems integration to the process of integrating more »

and ensemble models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking to explore diverse data sources for improved more »

smoothly work with AR solutions. Solid background in machine learning and AI, particularly in an AR setting. Proficiency in utilising machine learning frameworks like TensorFlow, PyTorch, and programming languages such as Python, Java, and C++. Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a more »

ecosystem (Lab, Notebook) and related libraries and tooling. • Python libraries for data management, statistical analysis, machine learning, and visualisation. • Machine learning frameworks such as TensorFlow and PyTorch. • Knowledge of Natural Language Processing and Computer Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning more »