26 to 50 of 306 Remote/Hybrid PyTorch Jobs

research and evaluate applicability to client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics ...

Community of Practice. Experience Required Essential Strong Python programming and hands-on experience with core ML/AI libraries (for example scikit-learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience deploying AI/ML in the cloud, particularly Microsoft Azure (Azure ...

environment.In-depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch).Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations.Mastery of SQL (including advanced optimisation techniques) and experience with relational ...

depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation techniques) and experience with ...

depth expertise in Python (Pandas, web scraping libraries such as Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation techniques) and experience with ...

GitHub, Docker/Kubernetes, MLflow, Jira. Edge deployments: Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators. Distributed model training & infra: Pytorch DDP, FDSP and TorchTitan, Megatron, Slurm, Run:ai, DeepSpeed, Kubernetes, cloud or on‐prem GPU clusters. About you You’ve built ML systems that persist—deployed ...

efficiency and delivery excellence.Connect to your skills and professional experienceTechnical Proficiency:Proven experience with Python and popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn.Strong understanding of machine learning algorithms, deep learning architectures, and statistical modelling techniques.Experience with cloud computing platforms (e.g., AWS, Azure, GCP or equivalent ...

/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 ...

technical leadership across the team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow ...

relevant AI fields.· Proven track record of designing, developing, and deploying AI systems in production environments.· Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).· Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. ...

collecting technology keywords. Useful experience Experience with some of the following would be valuable, but we do not expect you to know everything: PyTorch, TensorFlow or JAX Hugging Face LLM APIs and open-source models RAG and vector databases Apache Airflow AWS S3 ECS/EKS Redshift Docker Kubernetes GitHub ...

following areas would be highly beneficial: Machine Learning and AI Engineering Generative AI and Large Language Models Prompt engineering and context engineering scikit-learn, PyTorch or TensorFlow LangChain or similar AI frameworks Cloud data platforms and services across AWS, Azure or GCP Data warehouses and modern data platforms Big data ...

technical leadership level, leading engineering teams and influencing senior stakeholders. Strong hands-on experience with Python and modern AI/ML frameworks such as PyTorch and/or TensorFlow . Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases . Experience with frameworks and tooling such ...

with 1+ year hands‐on in LLMs/GenAI projects. Strong Python programming skills, especially in libraries such as Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow. Experience with OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar models. Knowledge of vector search, embedding models (e.g., BERT, Sentence Transformers), and semantic search ...

Docker), or software engineering best practices. Exposure to model governance, risk management, or MLOps practices. Experience with additional analytical tools or frameworks such as PyTorch, TensorFlow, R, or similar technologies. Master's degree in a quantitative or technical discipline, or equivalent practical experience. Job Posting End Date: Friday 11th September ...

leaders and connect operational bottlenecks to strategic AI solutions.Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers).Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

range of AI concepts, such as LLMs, VLMs, RAG, Agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Familiarity with machine learning frameworks (PyTorch, TensorFlow etc). Strong proficiency in software development (Python preferred) and strong understanding of data structures and algorithms. Engineering excellence - writing high-quality, maintainable code. ...

Python and modern software development practices.Hands-on experience with Distributed Training infrastructure (Multi-node GPU training, Kubernetes, vLLM).Familiarity with Deep Learning frameworks (PyTorch).Experience with MLOps tools and experiment tracking (e.g., ClearML, MLFlow, Weights & Biases).Research Fluency: Ability to read technical research papers and translate them into engineering requirements. ...

computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python including Pytorch, Tensorflow and SKLearn as well as initial knowledge of LangChain and RAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment ...

Python frameworks such as FastAPI.Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems.Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.A strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.Experience creating automated evaluations for generative ...

related field.Multiple years experience of delivering novel ML solutions to customers and internal stakeholders.Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.Experience of appropriate version control and environment management (such ...

related field.Multiple years experience of delivering novel ML solutions to customers and internal stakeholders.Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.Experience of appropriate version control and environment management (such ...

related field.Multiple years experience of delivering novel ML solutions to customers and internal stakeholders.Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.Experience of appropriate version control and environment management (such ...

related field.Multiple years experience of delivering novel ML solutions to customers and internal stakeholders.Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.Experience of appropriate version control and environment management (such ...