1 to 25 of 194 PyTorch Jobs

Master's degree in a related field required. Advanced experience developing and deploying machine learning models using Python and modern ML frameworks (e.g., Scikitlearn, PyTorch, TensorFlow). Strong applied expertise across core ML techniques, including regression, tree based models, clustering, deep learning, and NLP. Familiarity with generative AI and LLMs ...

Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative ...

with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry). Hands‐on experience with PyTorch, leading LLM libraries such as Hugging Face, LangChain, LangGraph, and LlamaIndex. Skilled in hypothesis formulation, defining evaluation metrics, conducting literature reviews and building reproducible prototypes ...

with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry).* Hands-on experience with PyTorch, and leading LLM libraries such as Hugging Face, LangChain, LangGraph, and LlamaIndex.* Skilled in hypothesis formulation, defining evaluation metrics, conducting literature reviews, and building reproducible ...

several of the following: Commercial experience developing AI or Machine Learning solutions Strong Python development skills Experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience ...

/CD, containerisation, monitoring, and deployment automation. Proficiency in Python and/or R, with experience using machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with modern AI frameworks such as FastAPI, LangChain, LlamaIndex, or similar technologies. Hands-on experience with LLM APIs, foundation models, embeddings, vector ...

Requirements Vetting: Active SC Clearance and British Citizenship are mandatory for this consultancy role. Core Tech: Solid professional experience with Python and frameworks like PyTorch, TensorFlow, or Scikit-Learn. GenAI: Hands-on experience developing LLM-based applications, RAG pipelines, and prompt engineering. Infrastructure: Experience deploying applications in cloud environments ...

/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization and orchestration ...

parallel and high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads. AI Software, MLOps & Generative AI ML frameworks: PyTorch and TensorFlow at a working, hands-on level. Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM ...

continuous improvement of AI performance, reliability and scalability. Requirements Commercial experience developing AI or Machine Learning solutions. Strong Python development skills. Experience with TensorFlow, PyTorch or similar ML frameworks. Knowledge of Computer Vision, Robotics or Autonomous Systems. Experience working with cloud platforms (AWS, Azure or GCP). Understanding of APIs ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such as Snowflake, BigQuery, or Databricks. ...

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 ...

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 ...

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 ...

efficient code for AI/ML solutions. Hands-on experience, through study, internships, or personal projects, with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Exposure to supporting the deployment of AI/ML models, working alongside engineering colleagues. Some exposure to generative AI concepts and tools (e.g., OpenAI ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with PyTorch and related data science Python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...

methods. Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. Tech Stack Python, SQL, pandas/numpy/scipy, PyTorch/sklearn Airflow/dbt, Kafka (or equivalents), Postgres/BigQuery Docker, Kubernetes (optional), CI/CD (GitHub Actions) Observability: Prometheus/Grafana, OpenTelemetry ...

Data Science, Machine Learning, Data Engineering, or Software Engineering roles Strong production Python experience Hands‐on experience training and serving ML models Familiarity with PyTorch, TensorFlow, or scikit‐learn Strong working knowledge of Docker, Linux, Git, and cloud platforms (AWS, Azure, or similar) Experience deploying systems you’ve helped design ...

technical solutions clearly to non-technical stakeholders Contribute to best practices around coding standards, maintainability and AI-assisted development Tech Stack Python, SQL, TensorFlow, PyTorch, AWS, Azure, Microsoft Fabric, NLP, LLMs, MLOps What We're Looking For Strong commercial Data Science experience Experience building and deploying ML models into production ...

Learning and ideally Azure AI Foundry Good understanding of MLOps and LLMOps Excellent Python engineering skills with experience using frameworks such as LangChain, LangGraph, PyTorch and Pydantic Experience with RAG, vector search, embeddings, prompt engineering and enterprise retrieval architectures Experience building AI solutions within document-heavy environments such as legal ...

LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options ...

Language Model (LLM) deployment and hosting Retrieval Augmented Generation (RAG), vector databases, semantic search and embedding techniques Python development and AI frameworks such as PyTorch, TensorFlow and LangChain MLOps frameworks and AI model lifecycle management API integration and enterprise-wide AI solution delivery Presenting architecture solutions to senior stakeholders, governance ...

Essential BSc in Machine Learning, Data Science, Computer Science, Mathematics or a related field. Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch). Experience delivering ML solutions to stakeholders. Good understanding of AI/ML algorithms for different data types and tasks, including Generative ...

system integrations — with a strong focus on GenAI, NLP, computer vision, and multimodal AI applications. Leverage deep knowledge of AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and enterprise architecture best practices (e.g., microservices, APIs, cloud-native design). AI & Data Platform Architecture/Deployment: Architect robust, secure ...