1 to 25 of 231 PyTorch Jobs

Technical Skills Working production experience in Python, and at least two of: C#, C/C++, Java, Go Machine Learning & AI stacks, including: TensorFlow, PyTorch, Scikit-learn, Transformers, LLMs. Customization: fine-tuning, RAG, other related methods. MLOps & DevOps: MLflow, TFX, Kubeflow, Docker, Kubernetes, CI/CD terminology and pipelines ...

including supervised, unsupervised, and reinforcement learning approaches Strong proficiency in statistical modelling, time‐series forecasting, and predictive analytics Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine‐tuning techniques Familiarity with distributed computing frameworks (eg Spark) Knowledge of graph neural ...

Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles ...

including supervised, unsupervised, and reinforcement learning approaches Strong proficiency in statistical modelling, time‐series forecasting, and predictive analytics Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine‐tuning techniques Familiarity with distributed computing frameworks (eg Spark) Knowledge of graph neural ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases ...

Deliver production-grade AI solutions in complex, regulated environments Accelerate outcomes using pre-built frameworks and accelerators Core Capabilities AI/ML Engineering: TensorFlow, PyTorch, XGBoost, transformer architectures MLOps & LLMOps: MLFlow, Kubeflow, SageMaker, KServe, vector DBs Cloud & Platform Engineering: AWS, Azure, GCP, Kubernetes, Terraform Data Platforms: Spark, Kafka, Snowflake, Airflow ...

through metrics like Character Error Rate (CER) and Word Error Rate (WER) is also crucial. Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Understanding of ML architectures, hyperparameter tuning, and performance optimisation. Experience with MLOps tools and CI/CD pipelines. Familiarity with data engineering concepts ...

Strong Python, API/microservices development, GCP (Vertex AI, BigQuery), CI/CD, and containerisation (Docker, Kubernetes) Nice to have: ML frameworks (PyTorch, TensorFlow, Hugging Face), MLOps practices, API Gateway/ISTIO, IAM/data governance, Responsible AI standards AI Architect Position Contract Length - 6 months (potential for extension) Location ...

building and managing CI/CD pipelines and MLOps workflows for machine learning. Strong Technical Foundation: Proficient in Python, common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and cloud platforms (AWS, Azure, or GCP). Preferred Qualifications: Advanced Degree: A Master's or Ph.D. in a relevant quantitative field. Healthcare ...

Spark, Airflow, or similar tools) Hands-on experience with cloud platforms (AWS, Azure, or GCP) Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Experience with data visualization and BI tools Strong problem-solving skills and ability to communicate technical concepts to non-technical stakeholders Preferred Qualifications Experience with ...

deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g., scikit-learn, MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level). Consulting Skills Skilled at asking the right questions to uncover technical requirements, constraints, and business drivers. Can translate ...

based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries (e.g. Pytorch, Tensorflow) from early conceptualisation to full deployment in scalable production environments Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements ...

GitHub Copilot, focusing on AI specification‐driven approaches for technical analysis, code generation, and code review. Hands‐on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (PydanticAI, LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

Proven experience as a Machine Learning Engineer within central government or regulated environments Strong programming skills in Python (e.g. Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) Experience building and deploying ML models into production environments Strong knowledge of cloud platforms, particularly: Azure (ML Studio, Azure ML, Data Factory, Synapse) Experience ...

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 ...

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 ...

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 ...

strong software engineering practices* Demonstrated expertise in building production-quality code and data pipelines for ML systems* Proficiency in modern AI development frameworks including: PyTorch, Jax , HuggingFace Transformers, LLM APIs (litellm etc) and vLLM for building and deploying large-scale AI applications* Understanding of LLM training methodologies including instruction fine ...

production Tech environment includes: Python AWS/Azure/GCP Kubernetes & Docker FastAPI Infrastructure as Code CI/CD pipelines ML frameworks such as PyTorch/TensorFlow What they’re looking for: Strong Python engineering experience Experience deploying ML models into production Cloud and containerisation experience Excellent communication skills Someone ...

/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. ...

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 ...

large data sets.Strong knowledge of hands-on practice in Python. Familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch and TensorFlow. Experience with MLFlow, AWS SageMaker and Bedrock is preferred.Good written and oral communication skills, including the ability to communicate across business areas ...