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Architect end-to-end generative AI solutions (LLM training, deployment, RAG workflows) on NVIDIA hardware, working directly with customers and internal engineering teams to design and optimize large language model systems.
Principal AI Engineer at Snowflake’s Cortex CoWork team, defining AI-driven enterprise data solutions. Focuses on agentic reasoning, NL-to-SQL, and scalable RAG systems for Fortune 500 clients, leading technical strategy and mentoring engineers.
Build and deploy reinforcement learning policies for a humanoid robot platform, iterating directly on physical hardware and closing the sim-to-real gap.
Build and deploy AI models and APIs to support Merck’s R&D, manufacturing, and supply chain teams using Python, cloud services, and modern ML practices.
Leads AI architecture and development of agentic/Generative AI systems, including LLM-powered agents, RAG pipelines, and multi-agent workflows, while mentoring engineers and collaborating cross-functionally to deliver scalable, production-grade solutions.
Builds and maintains automated evaluation suites to test AI trustworthiness (bias, explainability, safety) for Gemini-based agents, ensuring compliance and blocking releases with failing checks.
Research and deploy LLM-based solutions (e.g., RAG, fine-tuning) to optimize industrial processes, analyze technical documents, and mine scientific knowledge for Air Liquide’s energy and healthcare operations.
Lead a governed agentic AI platform’s delivery in JP Morgan’s Markets Operations, owning release calendars, cross-team dependencies, and metrics frameworks for production systems. Bridge engineering, product, controls, and operations to ensure safe, measurable releases while defining industry-leading measurement standards for agentic systems.
Design and implement AI models for aquaculture using computer vision and deep learning to analyze aquatic species traits from imaging data.
Builds and maintains automated evaluation suites for AI trustworthiness checks (e.g., explainability, bias, safety) across Gemini-based agents, ensuring compliance and audit readiness via CI/CD pipelines.
The Distinguished AI Engineer will lead the design and deployment of large-scale AI systems, including LLMs and agentic platforms, to modernize enterprise infrastructure. The role involves setting technical standards and mentoring teams while working in a hybrid office environment.
The Senior AI Engineer designs and deploys scalable, production-ready AI solutions using Python, LLMs, RAG, and Azure cloud infrastructure. This role involves leading technical initiatives, implementing MLOps practices, and collaborating with cross-functional teams to deliver measurable business value.
The ML Ops & LLM Ops Engineer will design and manage deployment architectures for AI solutions on AWS, focusing on CI/CD, infrastructure as code, and production-grade LLM/agentic application scaling. This role involves working as a forward-deployed engineer within enterprise client environments to ensure secure, observable, and efficient AI service delivery.
The Senior AI Engineer will design, develop, and deploy AI and machine learning solutions, including LLMs and RAG applications, for global clients. The role requires strong Python skills and experience managing the full ML lifecycle within a consulting environment.
Data/AI Engineer VP building scalable, data-driven software solutions for Barclays' Liquid Financing business, primarily using Python/Java, AWS services, Kubernetes, and AI/ML integrations.
Job Description Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.…
The Engineering Lead will spearhead the evolution of data technologies through Applied AI, designing and delivering scalable software solutions while managing teams and technical strategy. The role requires expertise in AWS, Python, and modern AI frameworks like LangChain and RAG to drive innovation within the bank's digital landscape.
NVIDIA is seeking Ph.D. students for research internships focused on generative AI, including multimodal models, diffusion models, and large language models. Interns will design algorithms, collaborate with research teams, and contribute to prototypes or publications while working with advanced AI technologies.
The Lead AI Engineer will design and implement LLM-enabled systems, including RAG architectures and agent workflows, while establishing technical standards and CI/CD pipelines for AI services. The role involves leading engineering teams to deliver scalable, secure, and observable AI solutions on AWS within a regulatory environment.
Design and build AI-powered software solutions using Java, Python, or .NET, focusing on microservices, containers, and cloud platforms.
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