76 to 100 of 361 TensorFlow Jobs

PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other More ❯

PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other More ❯

PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other More ❯

PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other More ❯

PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. - Experience using Python and hands on experience building models with deep learning frameworks (i.e., Tensorflow, Keras, PyTorch, MXNet). - Experience building applications leveraging GenAI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other More ❯

or similar) - 5+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch) PREFERRED QUALIFICATIONS - AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation) - AWS Professional certifications (e.g. More ❯

year hands-on experience in AI or ML in a professional environment (3-5 years preferred) Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) Solid programming background with experience using statistical and signal analysis libraries Experience with neural network architectures including deep learning models Understanding of transformer architectures and attention More ❯

into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS More ❯

into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS More ❯

cloud computing infrastructure. Experience with Computer Vision, image processing and video analytics. Experience with Natural Language Processing/Natural Language Understanding. Experience with deep learning framework and infrastructure like TensorFlow or PyTorch. Experience and/or willing to learn advanced techniques in Agentic A.I. framework and Large Language Models (LLMs). Experience and/or willing to research, develop More ❯

excellent 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 includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be More ❯

Advanced experience with SQL for 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, including Snowflake. Understanding of personalization More ❯

experience implementing ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in More ❯

experience implementing ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in More ❯

experience implementing ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in More ❯

Python. Rust and C++ are nice to have. 3+ years designing and building data-intensive solutions with distributed computing. 2+ years with industry-recognized ML frameworks (scikit-learn, PyTorch, TensorFlow, Spark, Ray). 1+ year productionizing, monitoring, and maintaining models. Bachelor's degree or equivalent work experience. Preferred Qualifications: 1+ years building, scaling, and optimizing ML systems. 1+ years More ❯

language processing or reinforcement learning Proven track record applying AI and ML to solve complex business problems, ideally in marketing, advertising or e-commerce Strong proficiency in Python (PyTorch, TensorFlow, scikit-learn), SQL and cloud ML orchestration environments such as AWS, Databricks or Flyte Experience with search marketing, ad auctions, bidding optimisation or customer segmentation is a plus Skilled More ❯

Demonstrated ability to fine-tune and optimize LLMs for quality, latency, sustainability and cost-effective performance. Programming and NLP Tooling: Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain. MLOps and Deployment: Experience with containerization tools (Docker, Kubernetes) and workflow management tools (Azure ML Studio, MLFlow). Cloud and AI Infrastructure: Hands-on experience More ❯

year hands-on experience in AI or ML in a professional environment (3-5 years preferred) • Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) • Solid programming background with experience using statistical and signal analysis libraries • Experience with neural network architectures including deep learning models • Understanding of transformer architectures and attention More ❯

with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in at least one ML framework, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production environments; knowledge of More ❯

including solid experience with software testing (unit, integration, system), and knowledge of test-driven development; other languages are a plus. Proficiency in ML frameworks, such as scikit-learn, XGBoost, Tensorflow, or PyTorch. Proficiency with Cloud platform(s), such as Google Cloud Platform, Amazon Web Services, or Azure. Experience in designing, and deploying ML pipelines in production environments; knowledge of More ❯

Exploratory Data Analysis, Transfer Learning, Computer Vision, Image Processing, Image Classification, Object Detection, YOLO v8, SAM, Stable Diffusion (2.1, 2.x, tiny-SD) Frameworks: Python (scikit-learn, pandas, NumPy), Keras, TensorFlow, Pyspark, Streamlit Data Visualization Tools: Matplotlib, Seaborn, Advanced Excel Cloud: S3, Lambda, API Gateway, EC2, Athena, Glue, OpenSearch, Bedrock, SageMaker, Azure Functions, Azure SQL, Azure ML Studio, GCP Vertex More ❯

Responsibilities Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯

Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯

Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯