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Design and deploy production-grade GenAI and ML solutions on AWS, optimizing cost, security, and performance while embedding reusable patterns into DoiT’s Cloud Intelligence platform.
Design and deploy production-grade GenAI and ML solutions on AWS for enterprise customers, focusing on cost efficiency, reliability, and security while creating reusable patterns and driving product adoption.
Build and own critical React-based frontend components for Scale’s AI platform, integrating with Node.js/Python backends and distributed data pipelines to power large-scale AI model training and evaluation.
Build and deploy robust backend services that expose, orchestrate, and supervise AI solutions like conversational agents, RAG pipelines, and NER extractors in Python.
Designs and builds reinforcement-learning training environments, defines reward functions, and validates data quality to train and evaluate AI agents across domains.
Build and deploy AI/ML models for a public-sector client, focusing on OCR, object detection, and LLM fine-tuning using Python, PyTorch, Hugging Face, and AWS serverless tools.
Lead a team to build enterprise-scale generative AI and agentic systems using LLMs, RAG, and multimodal pipelines for Mastercard’s Business & Market Insights group.
Lead NVIDIA’s GenAI data strategy, defining how diverse datasets fuel and align large-scale AI models, and partnering with research teams to refine data pipelines and synthetic generation.
Research and build agentic LLMs and reinforcement-learning systems for code generation, running experiments, curating datasets, and shipping production-quality research code.
Principal AI/ML Research Engineer leads applied research in generative AI, deep learning, and Transformers to build Payment Foundation Models for commerce and fintech challenges, driving novel architectures from prototype to production.
About us We are building AI systems that can reason, use tools, and complete meaningful work in the real world. Our team works across model post-training, reinforcement-learning infrastructure, large-scale training,…
Builds and shares tutorials, workshops, and code samples to teach developers how to integrate AWS generative AI tools like Amazon Q and Bedrock into their workflows.
Design and advise on scalable, cloud-native GenAI and Agentic AI architectures for AWS customers, integrating LLMs, RAG, and MLOps while driving adoption and best practices across industries.
Build and scale foundational large language models for Amazon’s shopping experiences, focusing on ML infrastructure, post-training, and reinforcement learning to improve personalization and customer interactions.
Build and improve ML systems that power Macroscope’s AI features, focusing on evaluation datasets, experiments, and model training to enhance codebase insights.
Leads Apple’s ML/NLP team to develop and scale agentic workflows for personalized writing tools, summarization, and keyboard features (autocorrection, proofreading) across all Apple platforms and languages, bridging cutting-edge AI research with real-world product experiences.
Role Title: LLM Red-Teamer Role Type: Contractor Location: Remote micro1 is engaging LLM Red-Teamers to contribute to a high-impact customer project focused on the evaluation and improvement of frontier language…
Role Title: AI Evaluation Analyst Role Type: Contractor Location: Remote micro1 is engaging AI Evaluation Analysts to contribute to a customer’s project focused on advancing frontier language model capabilities. In…
Build and deploy large-scale machine learning models and AI agents to optimize Micron’s semiconductor manufacturing workflows using distributed training and GPU optimization techniques.
Builds and optimizes generative AI models and agentic workflows using fine-tuning, RAG, and hybrid architectures for low-latency applications.
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