1 to 25 of 389 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 ...

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 ...

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 ...

enhance predictive accuracy, interpretability, and automation. Engineer scalable analytical frameworks and reusable ML assets, integrating Python-based (or other) ML pipelines (TensorFlow, PyTorch, Scikit-learn, Pandas) with enterprise data platforms (Snowflake, Azure, Google Vertex AI) to standardise insight generation and model delivery. Collaborate with Data Architecture and Engineering ...

enhance predictive accuracy, interpretability, and automation. Engineer scalable analytical frameworks and reusable ML assets, integrating Python-based (or other) ML pipelines (TensorFlow, PyTorch, Scikit-learn, Pandas) with enterprise data platforms (Snowflake, Azure, Google Vertex AI) to standardise insight generation and model delivery. Collaborate with Data Architecture and Engineering ...

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 ...

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 ...

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 ...

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 ...

evaluation) Solid track record in speech/audio processing, e.g. ASR, TTS, speech enhancement, audio analysis, NLP-audio interfaces, etc Experience with PyTorch or TensorFlow Strong engineering fundamentals: Git, CI/CD, testing, code quality, agile workflows Ability to take research concepts through to production-ready implementations Strong communication ...

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 ...

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 ...

maintainable code Solid understanding of ML fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metrics Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases ...

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 ...

Generative AI, Agentic AI and reinforcement learning. Strong proficiency in programming languages, particularly Python. Expertise in AI/ML frameworks such as PyTorch/TensorFlow, Scikit-learn, Statsmodels, LangGraph and ADK. Familiarity with cloud platforms (preferably Google Cloud Platform and Vertex AI). Strong analytical, critical thinking, and complex ...

Generative AI, Agentic AI and reinforcement learning. Strong proficiency in programming languages, particularly Python. Expertise in AI/ML frameworks such as PyTorch/TensorFlow, Scikit-learn, Statsmodels, LangGraph and ADK. Familiarity with cloud platforms (preferably Google Cloud Platform and Vertex AI). Strong analytical, critical thinking, and complex ...