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Lead - Machine Learning
- New York, New York, United States
- New York, New York, United States
Über
East Coast (USA) Responsibilities
Define and design comprehensive end-to-end architecture for production-grade multi-agent systems that are reliable, well-governed and compliant with industry standards. Establish architectural standards, patterns and best practices for multi-agent deployments. Create technical roadmaps and architecture blueprints for enterprise-grade agentic solutions. Standardize proof-of-concept Agent codebases into robust, scalable, production-ready solutions. Establish testing frameworks for multi-agent system validation. Design and implement robust deployment pipelines on AWS/Azure cloud platforms. Ensure scalability, reliability and performance of multi-agent systems in production. Establish monitoring, logging and alerting systems for production environments. Implement security protocols and compliance measures for enterprise deployments. Conduct risk assessments and develop mitigation strategies for production systems. Ensure adherence to data privacy and regulatory requirements. Conduct Technical Reviews and ensure code quality across all development phases. Guide development teams on orchestration patterns, error handling, CI/CD readiness, and scalability. Help customers with creating sustainable, enterprise-grade AI architectures that deliver measurable business value. Serve as an advisory consultant to customers on their AI transformation journey, collaborating with Technical specialists and Business Development teams. Develop technical content, reference implementations, and presentations to enable customers fully leverage AI/ML and Generative AI on Azure/AWS. Develop and execute strategic roadmaps for LLM-based solutions, including RAG, Agentic RAG, and Agent-driven workflows. Guide AI model evaluation, MLOps pipeline integration, and fine-tuning strategies for scalable AI solutions. Skill Set Required
Proficiency in LangGraph, LangChain for agentic workflows. Deep technical experience across the AI spectrum from traditional ML and deep learning to Generative AI and Agentic AI. Hands-on experience with autonomous agent frameworks and developing multi-agent systems. Experience with AWS or Azure (LLM hosting, GPU-based inference, cost optimization). Mentoring team members for career progression and upskilling to drive better solution outcomes. Understanding of governance frameworks (e.g., AI Ethics, Explainability, Risk Mitigation). What is in it for you
Be part of a team with a strong track record in production AI applications on DGX and Cloud GPUs. Peer learning and accelerated growth in Applied AI and GPU computing, plus technical communication skills. Exposure to Fortune 500 leaders and market disruptors transforming their businesses with Generative AI. Access to state-of-the-art GPU infrastructure on the cloud and on-premise. Work with a rapidly growing AI-first digital transformation and engineering company. Seniority level
Mid-Senior level Employment type
Part-time Industries
IT Services and IT Consulting
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Sprachkenntnisse
- English
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