1 to 25 of 1,056 PyTorch Jobs

deployment (e.g., containers, Kubernetes) Deep expertise in machine learning and deep learning, particularly transformer-based models and LLMs Hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX) and distributed training (DeepSpeed, FSDP, Horovod) Proven ability to integrate AI capabilities into existing and legacy enterprise systems (e.g., legacy CMS or COTS ...

application services (e.g., Amazon Bedrock, SageMaker, Lambda, DynamoDB). Exposure to the Python data and ML ecosystem (e.g., Pandas, NumPy, and libraries such as PyTorch, TensorFlow, or Scikit-learn). Familiarity with RESTful APIs, web services, and third-party or system integrations. Understanding of AI model and prompt evaluation, monitoring ...

quality assessment**.* Good foundation in **statistics, probability, optimization, experimentation, and applied machine learning**.* Advanced proficiency in Python and modern AI frameworks, including **PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems**.* Experience building and scaling **enterprise AI platforms, ML infrastructure, and intelligent applications serving ...

microservices. Git and software development practices. Secondary Skills Cloud platforms: AWS/Azure/GCP . Docker and Kubernetes. ML frameworks such as PyTorch or TensorFlow . MLOps and model deployment. SQL and NoSQL databases. AI agents and tool/function calling. Knowledge of LLM evaluation and observability tools. Education ...

responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. D ESIRABLE : Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

bring experience in managing, coaching, and developing junior members of a team and wider community. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g, GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

efficient, and maintainable code to enable scalable and production-grade AI/ML solutions. Extensive experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), with the ability to design, implement, and optimise scalable solutions while guiding teams in the effective use of these tools. Extensive expertise in designing, deploying ...

evaluating, and deploying open-source and proprietary LLMs, embedding models, and vector databases (e.g., Pinecone, Milvus, Qdrant, FAISS). Programming & Frameworks: Proficiency in Python, PyTorch, TensorFlow, LangChain, LlamaIndex, and modern API frameworks (FastAPI, RESTful APIs). Data Pipelines & Databases: Experience working with complex structured and unstructured data sources, SQL, NoSQL ...

C++.Experience with machine-learning, deep-learning, computer-vision, and generative-AI frameworks.Proficiency in ML modeling frameworks and libraries such as scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, YOLO, Detectron, Hugging Face, or equivalent with natural-language-processing techniques, including text classification and language developing and evaluating image-analysis models using image ...

sized for training and checkpointing workloads. AI Software, MLOps & Generative AIOrchestration & containers: Kubernetes, Docker, Slurm, Run:ai or equivalent GPU scheduling platforms. 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 ...

testing and Infrastructure as Code. Excellent communication and stakeholder management skills. A passion for mentoring and developing other engineers. Technology Stack Python SQL FastAPI PyTorch Docker Kubernetes AWS Azure Git CI/CD Knowledge Graphs Large Language Models (LLMs) Amazon Bedrock Azure AI Foundry Machine Learning Natural Language Processing ...

establishing best practices for software development, including agile methodologies, CI/CD, and DevOps/MLOps workflows. Proficiency with ML/AI frameworks (PyTorch, TensorFlow, scikit-learn), LLM deployment, cloud platforms (AWS, Azure, GCP), and modern development tools including containerization (Docker, Kubernetes) and streaming data platforms (Kafka, Spark). Strong ...

/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 ...

detection Expert experience developing ML algorithms - supervised/unsupervised learning, neural networks, and NLP - with hands-on expertise in at least one major framework (PyTorch or TensorFlow) and the broader Python ML stack (scikit-learn, pandas, NumPy) Expertise in Data Engineering - Data cleaning, feature engineering, preventing data leakage What Would ...

parallel processing. Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins). Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience with cloud-native architecture and software API design. Experience integrating machine learning into operational DoD systems or edge computing environments. Familiarity ...

roles Strong experience building and deploying LLM-based applications in production environments Solid expertise with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar Strong understanding of transformer architectures, LLM fine-tuning, prompt engineering, RAG systems, and vector databases Experience building scalable ...

implement models, optimize performance, and manage training pipelines effectively. Technical Proficiency: Proficiency in programming languages commonly used in AI development, such as Python, TensorFlow, PyTorch, or similar tools, along with modern LLM/agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon ...

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 ...

deploying AI applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

agents.What you’ll bring5+ years of experience in AI, Machine Learning, Data Science, or related fields.Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, and Hugging Face.Experience taking AI proof-of-concepts from idea to production.Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine ...

scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing ...

scale production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity ...

scale production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity ...

model APIs. Experience evaluating model outputs, accuracy, reliability, latency, and other AI performance considerations. Experience with AI/ML frameworks or libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar technologies. Experience with REST APIs, microservices, event-driven systems, or backend frameworks. Experience with SQL, NoSQL databases, data ...

model APIs. Experience evaluating model outputs, accuracy, reliability, latency, and other AI performance considerations. Experience with AI/ML frameworks or libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar technologies. Experience with REST APIs, microservices, event-driven systems, or backend frameworks. Experience with SQL, NoSQL databases, data ...