1 to 25 of 104 Remote TensorFlow Jobs

and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits More ❯

/Astra DB, Data modeling, ETL * Cloud & DevOps: AWS (S3, SageMaker), * Tools & Frameworks: Git, Jira, Confluence, PyCharm, Notebooks * Machine Learning and Deep Learning: Pandas, NumPy, Scikit-Learn, OpenCV, PyTorch, Tensorflow, OpenCV * GenAI/LLMs: Hands-on experience with generative AI tools and frameworks Geospatial Tools: Experience with GIS platforms such as ArcGIS, QGIS, CARTO or geospatial libraries in Python More ❯

iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting More ❯

iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting More ❯

production-grade AI/ML and Generative AI solutions; evidence of real-world impact highly desirable. Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred. Deep understanding of LLMs, prompt engineering, RAG More ❯

Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data More ❯

AI/ML Data, Tools Development Proficiency in Python, with a background in back end services and data processing Exposure to AI/ML algorithms Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) Understanding of LLMs, vector databases, and retrieval systems Experience with Model Context Protocol (MCP) integration and server development Big Data & Cloud Infrastructure Knowledge of building and More ❯

developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it for More ❯

strategic value Qualifications Experience Extensive experience in data science, machine learning, or advanced analytics, ideally in a technical leadership role Proven expertise in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and experience across NLP, computer vision, and LLMs Strong statistical foundation, including A/B testing, causal inference, and experimental design Proficiency in SQL and working with More ❯

from structured and unstructured data. Build data pipelines, models, and AI 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 complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

from structured and unstructured data. Build data pipelines, models, and AI 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 complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

from structured and unstructured data. Build data pipelines, models, and AI 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 complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

from structured and unstructured data. Build data pipelines, models, and AI 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 complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with 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 ❯

around ML model management. Strong knowledge of SQL and database management, as well as programming languages such as Python, R, or similar. Strong experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn) as well as familiarity with data technologies (e.g., Hadoop, Spark). About Vixio: Our mission is to empower businesses to efficiently manage and meet their regulatory obligations More ❯