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Hands-on technical leadership role designing and delivering production-grade Generative AI and Agentic AI solutions, including LLM-powered applications, RAG pipelines, multi-agent architectures, and LLMOps using Python, agent frameworks, and cloud platforms.
Leads AI-driven development of insurance products by designing agentic AI systems, optimizing LLM inference, and delivering full-stack features.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of…
AI Consultant providing technical leadership for building and deploying scalable ML/LLM/SLM applications—including RAG pipelines, custom agents, multimodal systems, and cloud/MLOps infrastructure—on a part-time remote contract basis.
The LLM Engineer will design and operationalize fine-tuning workflows for large language models using techniques like RLHF and DPO. The role involves building scalable training pipelines, managing GPU cluster operations, and collaborating with cross-functional teams to deliver production-grade AI solutions.
An AI Forward Deployed Engineer embedding with enterprise clients to build production-grade applications on proprietary foundation models, involving RAG pipelines, model fine-tuning, agentic workflows, and inference optimization using Python, PyTorch, vector databases, and cloud infra.
Senior AI Engineer designing, building, and optimizing AI agents, RAG pipelines, and fine-tuning LLMs using Python, PyTorch/Hugging Face, and vector databases.
Build the evaluation/judgement layer for AI agent trajectories at Moveworks/ServiceNow — designing LLM judges, rubrics, calibration loops, and process reward models so that evaluation scores can be used as training signals. Core tech: LLMs, Python, fine-tuning, reward modeling.
Lead the design and operation of scalable data pipelines that ingest, process, and deliver multimodal training data for AI models, ensuring quality and reliability for model development.
Build real-time multimodal AI models (text, audio, vision) using RLHF/PPO and post-training techniques to power next-gen agentic systems and hardware.
Build and improve multimodal AI models that understand and generate text, images, and video for real-time user experiences.
Build post-training strategies (RL-based) to train coding and agentic AI models, including reward modeling, simulation environments, and evaluation frameworks.
Design and build RL environments, reward functions, and task curricula to train and evaluate proactive personal AI agents, scaling infrastructure for large-scale training runs at an AI/hardware company.
Develop evaluations, benchmarks, and diagnostic methods to identify and analyze failure modes in frontier LLMs and multimodal models, applying post-training expertise (SFT, RLHF, reward modeling) and publishing research at top AI conferences.
Research and develop post-training techniques (SFT, RLHF, reward modeling) to improve large language and multimodal models, publish findings, and collaborate with top AI labs.
Owns AI product delivery for military planning and real-time alerting systems, driving deployments in classified environments and translating operational needs into platform requirements.
Develops and operates production-grade multi-agent systems and autonomous workflows, focusing on RAG architectures, knowledge graphs, and hybrid retrieval strategies for AI-driven document processing and LLM optimization.
Role: GenAI Lead Engineer Experience: 8+ years total (with significant hands-on GenAI / LLM work) Job Overview: We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the…
Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design,…
Design, generate, evaluate, and improve LLM training data (instruction, preference, reasoning, domain-specific) and build automated synthetic data generation pipelines using Python and LLMs.
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