1 to 25 of 345 PyTorch Jobs

implementation experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

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 ...

Processing, Generative AI, and advanced analytical techniques • Proficiency in Python and experience with AI and data science frameworks such as pandas, scikit-learn, TensorFlow, PyTorch, or LangChain • Experience developing and deploying AI models into production environments • Solid understanding of data engineering principles, including data preparation, integration, and deployment pipelines • Knowledge ...

Generative AI, Natural Language Processing, Advanced Analytics, and ideally Computer Vision. Excellent Python development skills with frameworks such as pandas, scikit-learn, TensorFlow or PyTorch, and LangChain. Experience with cloud AI services including AWS Bedrock, Azure Machine Learning, or Google Cloud AI Platform. Good understanding of data engineering, model deployment ...

experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.G. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/CD for ML, versioning, and monitoring ...

experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.g. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/CD for ML, versioning, and monitoring ...

async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile ...

using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication ...

Oversee the design and deployment of enterprise‐grade AI solutions using Python, .NET, and cloud‐based MLOps pipelines. Direct teams leveraging advanced frameworks including PyTorch, TensorFlow, Hugging Face, ONNX Runtime, and LangChain, integrating orchestration tools like Semantic Kernel, LangGraph, and CrewAI. Drive responsible integration of Large Language Models (LLMs) from ...

technical AI/ML projects, including team mentoring and project management. Expert level proficiency in Python and extensive experience with machine learning libraries (PyTorch, TensorFlow, Hugging Face transformers). Experience in Typescript is a plus. Strong understanding of natural language processing techniques, including text classification, named entity recognition, sentiment analysis ...

adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit‐learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES AND QUALIFICATIONS Responsibilities: Design, build, and maintain robust data pipelines for feature engineering ...

retrieval‐augmented generation, tool/function calling, agentic workflows), including evaluation and safety patterns. Expertise with machine learning frameworks and data science packages (e.g., PyTorch, TensorFlow, Scikit‐Learn, NumPy, Pandas, SciPy, statsmodels). Experience deploying to AWS (e.g., SageMaker, Bedrock) and operating production workloads with attention to cost, performance, security ...

frameworks. Strong proficiency in programming languages such as Python, Java, or Go, along with experience integrating with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch). Proven ability to translate complex business requirements into well‐defined, cloud‐optimized application architectures, scalable data models (e.g., relational, NoSQL, graph), and technical specifications ...

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 ...

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 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation ...

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 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation ...

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 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation ...

experience in AI/ML engineering with end-to-end project ownership Strong Python skills and hands-on experience with frameworks such as PyTorch, TensorFlow, or scikit-learn Experience with LLMs, Generative AI, and open-source models (GPT, Llama, Hugging Face, etc.) Knowledge of RAG architectures , vector search, embeddings ...

2+ years experience as an AI/ML Engineer on real projects Strong Python development skills and experience with ML frameworks (scikit-learn, TensorFlow, PyTorch, Hugging Face) Hands-on experience with Large Language Models (LLMs) such as GPT-4, Claude Sonnet, Claude Haiku, or similar foundation models Experience designing ...

monitoring in real-world applications. 3+ years of experience in AI & ML Engineering Strong proficiency in Python Strong proficiency in frameworks like TensorFlow, PyTorch, or Scikit-learn Experience with data pipelines and MLOps Cloud platforms (AWS, Azure, or GCP) Proven ability to develop and deploy ML models at scale Professional ...

approaches for standardised integration between AI applications, tools, and enterprise data sources Strong Python engineering skills, including experience with libraries and frameworks such as PyTorch, Pydantic, LangChain, and LangSmith Experience with prompt orchestration, structured outputs, evaluation, and tool-calling patterns for LLM applications Knowledge of RAG patterns, vector search ...

PySpark. Experience in using Data Science Platforms Experience using the latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker ) and frameworks (e.g. Tensorflow, PyTorch, MXNet, scikit-learn ) Good understanding of software architecture patterns & application development. Familiarity with DevOps,DataOps,MLOps, LLMOps principles including code repository, code management, CI/ ...

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. ...

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+ ...