1 to 25 of 359 TensorFlow Jobs

/AI engineering, with at least 5+ years focused on AI and ML system development. Strong expertise in machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch, Keras), and classical ML tools (Scikit-learn Hands-on experience building production-grade AI and data pipelines using cloud platforms (AWS, Azure ...

Support evidence-based decision-making across HR and the wider business. Skills And Requirements Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, and experience with AI frameworks for deep learning and generative models) and SQL. Experience working with HR data sources (Workday, SuccessFactors, Oracle HCM, LinkedIn ...

Exposure to observability/monitoring systems (Prometheus, Grafana, ELK, Datadog) is a plus. Proficiency in Python and familiarity with ML libraries (scikit-learn, XGBoost, TensorFlow, PyTorch). Strong experience with data manipulation and pipelines using Pandas, NumPy, and SQL. Knowledge of containerized deployments (Docker, Kubernetes) and cloud ML services ...

both technical and non-technical stakeholders. Preferred Qualifications: Deep understanding of various ML algorithms (supervised, unsupervised, reinforcement learning) and popular ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Deep understanding of MLOps principles and their implementation on GCP using tools like Vertex AI Pipelines. Experience with other major cloud ...

could be doing Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery ...

could be doing Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery ...

could be doing Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery ...

could be doing Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery ...

regression, classification, clustering, or time-series forecasting. Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow). Strong experience with SQL and data manipulation across large datasets. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI). ...

could be doing Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery ...

responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model ...

building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model ...

design for long-term scalability, reliability, and resilience. Has strong programming skills with Python - essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated ...

years. You must be able to hold or gain a UK government security clearance. Preferred Technical And Professional Experience Familiarity with machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms (AWS, Azure, Google Cloud). Knowledge of big data technologies (Hadoop, Spark). Background in supply ...

technical field Strong proficiency in Python 2-4 years of experience in machine learning or backend software development Hands on experience with ML frameworks (TensorFlow, PyTorch, Scikit learn) Solid understanding of ML workflows: data cleaning, model development, tuning, evaluation Familiarity with model deployment, API development, or real world ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

experimental design Proven ability to communicate technical solutions clearly to non-technical stakeholders Technical skills (a big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills ...

Cloud, or Azure) and modern DevOps practices (Infrastructure-as-Code). Proficiency with Git, Unix/Linux, Docker. Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn (commercial experience not essential). Excellent communication skills for both internal and client-facing interactions. Awareness of MLOps ...

distributed systems design. Proven experience designing or scaling AI/ML or LLM-based applications. Proficiency in one or more programming languages: Python, JavaScript, TensorFlow, Keras, PyTorch, TypeScript, or Node.js. Familiarity with modern AI frameworks (LangChain, LangGraph, Google ADK, Strands, Semantic Kernel, AutoGen, CrewAI, LlamaIndex). Understanding of Agentic ...

distributed systems design. Proven experience designing or scaling AI/ML or LLM-based applications. Proficiency in one or more programming languages: Python, JavaScript, TensorFlow, Keras, PyTorch, TypeScript, or Node.js. Familiarity with modern AI frameworks (LangChain, LangGraph, Google ADK, Strands, Semantic Kernel, AutoGen, CrewAI, LlamaIndex). Understanding of Agentic ...

areas such as speech recognition, speech enhancement, audio analysis, text-to-speech synthesis, and natural language processing. Proficiency with machine learning frameworks such as TensorFlow or PyTorch. Solid understanding of software engineering principles, including version control (Git), CI/CD pipelines, and agile development methodologies. Excellent communication, collaboration ...

areas such as speech recognition, speech enhancement, audio analysis, text-to-speech synthesis, and natural language processing. Proficiency with machine learning frameworks such as TensorFlow or PyTorch. Solid understanding of software engineering principles, including version control (Git), CI/CD pipelines, and agile development methodologies. Excellent communication, collaboration ...

experience training, deploying, and maintaining machine learning models in production Proficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

Proven expertise in time-series forecasting and spatio-temporal modeling, ideally applied to weather or energy systems. Strong proficiency in Python (Pandas, NumPy, PyTorch, TensorFlow, scikit-learn, Lightning, or equivalent). Solid understanding of data engineering and ML infrastructure Experience deploying ML models to cloud-native environments (Kubernetes, Docker ...