101 to 125 of 424 TensorFlow Jobs

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 ❯

models into production environments at scale. Expertise in Python and relevant ML libraries. Strong experience with various ML algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g., TensorFlow, PyTorch). Experience developing generative AI applications and deploying them into production. Experience working with cloud platforms, ideally Google Cloud Platform (GCP) and BigQuery. Proficiency in working with and More ❯

HITL) systems, annotation platforms, and quality review pipelines. Knowledge of satellite imagery analysis. Proficiency in remote sensing techniques and image classification. Familiarity with Python, R, MATLAB and libraries like TensorFlow, PyTorch, OpenCV. Familiarity with Convolutional Neural Networks (CNN)s, object detection, segmentation, and classification models. Familiarity with REST APIs and integrating models into web-based applications. Knowledge of satellite More ❯

HITL) systems, annotation platforms, and quality review pipelines. Knowledge of satellite imagery analysis. Proficiency in remote sensing techniques and image classification. Familiarity with Python, R, MATLAB and libraries like TensorFlow, PyTorch, OpenCV. Familiarity with Convolutional Neural Networks (CNN)s, object detection, segmentation, and classification models. Familiarity with REST APIs and integrating models into web-based applications. Knowledge of satellite More ❯

and storage and to explain trade offs to customer architects. You have experience selling new technologies with a focus on product adoption and expansion. Experience with ML, deep learning, TensorFlow, Python, NLP. Expertise in sizing and designing GPU clusters (pass through vsvGPU/MIG), including storage/network throughput considerations and reference configurations for training vsinference workloads. You have More ❯

and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT More ❯

and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT More ❯

or a related field 12+ years of experience in software engineering, with a focus on machine learning or natural language processing Strong expertise in deep learning frameworks such as tensorFlow, pyTorch, or MXNet Proficiency in programming languages such as python, C++, or java Solid understanding of LLM architectures, training techniques, and evaluation methodologies Familiarity with cloud platforms (e.g., AWS More ❯

Computer Science, Engineering, or a related field with a strong ML focus. Solid understanding of deep learning architectures (CNNs, RNNs, Transformers). Proficiency in Python and ML libraries like TensorFlow, PyTorch, and scikit-learn. Strong experience with AWS services and cloud-native development. A proactive, collaborative mindset with a passion for learning and innovation. Bonus Points For Familiarity with More ❯

to write production-grade code and a good understanding of data engineering & MLOps. Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch. Collaborative and humble team player with the ability to work with multi-functional teams, including technical and non-technical stakeholders. Passion for learning new skills and staying More ❯

Experience with sports data is ideal but not essential. Familiarity with sports performance and biometric data analysis would be nice. Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Scikit-learn. Any experience working with large, complex data sets and managing data pipelines, ensuring data quality and integrity. Some experience in data analysis, predictive modelling, or More ❯

building tools that get deployed and used. Key Responsibilities Develop and deploy ML models and pipelines that support national security missions. Engineer production-ready AI solutions using Python, PyTorch, TensorFlow, etc. in edge or cloud environments. Collaborate with software teams to containerize, optimize, and integrate models into full-stack systems using Docker, Kubernetes, or equivalent. Implement MLOps pipelines using More ❯

stability Extensive practical cloud native experience Strong programming skills in Python (especially scientific libraries: PyMC, NumPy, SciPy, pandas, etc.) and experience working with probabilistic programming frameworks (e.g. PyMC, Stan, TensorFlow Probability). Experience designing and deploying Bayesian networks, Monte Carlo simulations, or other probabilistic models in complex real-world systems. Demonstrated experience developing enterprise-scale data modelling platforms or More ❯

Java/Python, including API integrations Knowledge of RESTful API development and integration Understanding of version control systems (e.g., Git) Specific tools include: Python Libraries like Scikit-learn or TensorFlow SQL and NoSQL databases Soft skills include: Self-starter Collaborative Fast-paced and adaptable to change Attention to detail Strong problem-solving skills Excellent communication skills Passion for software 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 ❯

fine-tuning Large Language Models or interactive AI applications (>1 year post-graduate experience); Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g., Python, TensorFlow, PyTorch); Preferably several years of experience working with different AI capabilities and showcasing your passion both at work and outside work in the utilization of AI; Excellent communication skills 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 ❯

applications. Required skills: Solid foundation in AI/ML principles (e.g. neural networks, NLP, transformers, speech processing). Hands-on experience with Python and popular ML frameworks (e.g. PyTorch, TensorFlow, Hugging Face). Familiarity with LLM APIs and open-source models (e.g. GPT, Claude, Mistral, Whisper). Familiarity with agentic AI frameworks (LangChain, AutoGen, CrewAI, OpenAI Functions). Interest More ❯

stability Extensive practical cloud native experience Strong programming skills in Python (especially scientific libraries: PyMC, NumPy, SciPy, pandas, etc.) and experience working with probabilistic programming frameworks (e.g. PyMC, Stan, TensorFlow Probability). Experience designing and deploying Bayesian networks, Monte Carlo simulations, or other probabilistic models in complex real-world systems. Demonstrated experience developing enterprise-scale data modelling platforms or More ❯

to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying More ❯

to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying More ❯

the state-of-the-art generative AI based systems. You are comfortable with quickly prototyping and iterating your ideas to build robust ML models using technology such as PyTorch, Tensorflow, AWS Sagemaker, and SparkML. Our team is at an early stage, so you will have significant impact on our ML deliverables with little operational load from existing models/ More ❯

processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models - Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow PREFERRED QUALIFICATIONS - Masters or PhD degree in computer science, or related technical, math, or scientific field - Proven knowledge of Generative AI and hands-on experience of building applications with More ❯

data science, engineering, or computer science - 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 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We More ❯

enhance traditional natural language processing tasks, prompt engineering, integrating LLMs into machine learning workflows Strong Python skills and familiarity with libraries such as scikit-learn, pandas, NumPy, PyTorch or TensorFlow Advanced SQL skills and experience working with complex, high-volume datasets Practical experience with MLOps tools and practices for deploying and maintaining models Experience leading projects and collaborating across More ❯