26 to 50 of 243 PyTorch Jobs

Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert ...

driven systems Experience with CI/CD pipelines, testing, and containerisation Strong problem-solving and communication skills Technology Stack Python, SQL, FastAPI, PyTorch, Transformers/LLMs, Terraform, Databricks, Kubernetes, AWS, Azure, PostgreSQL, Kafka, Git, CI/CD, Knowledge Graphs What's on Offer Fully remote working within the UK Opportunity ...

machine learning solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application development Hands on experience with at least ...

track record delivering production AI/ML and GenAI at enterprise scale — real impact, not just prototypes Expert Python with hands-on experience in PyTorch, TensorFlow, LangChain, LangGraph, RAG pipelines, and LLMs Solid MLOps/LLMOps fundamentals: CI/CD for ML, model governance, and evaluation frameworks Broad cloud experience ...

OpenAI, Hugging Face, or similar Experience building and integrating AI-powered solutions into production systems Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar Familiarity with APIs, microservices, and cloud platforms (Azure, AWS, or GCP) Experience handling and processing large datasets Knowledge of prompt engineering, fine-tuning ...

pipelines, and LLM fine-tuning (OpenAI, LLaMA, Cohere, etc.). 3–5+ years building scalable web applications with React/TypeScript. Solid experience with PyTorch/TensorFlow, MLflow, and CI/CD pipelines. Excellent communication skills and the ability to work effectively within agile, cross-functional teams. This ...

Agentic AI systems LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks RAG pipelines and vector databases AI agents and multi-agent orchestration Python, PyTorch, TensorFlow, Scikit-learn Cloud AI platforms such as AWS, Azure, or GCP Production deployment, MLOps, and scalable AI infrastructure API integration and workflow automation Bonus Points ...

learning solutions for personalizing recommendations. Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus. You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing and improving large scale ...

Skills & Experience BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch). Have an established track record of delivering ML solutions to customers and internal stakeholders. Demonstrate deep understanding of AI/ML algorithms for different ...

selecting appropriate modeling approaches for each. Strong proficiency in Python and SQL, with hands‐on experience using major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit‐learn) for model development and evaluation. Deep understanding of machine learning algorithms, model evaluation techniques (e.g., AUC, lift, calibration, stability), and data pipeline development ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

data scientists, software engineers, and product managers to identify and quantify risks associated with models Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi-modal ...