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Title: Sr Machine Learning Engineer
Location: Remote EST or hybrid in Raleigh, NC
Duration: 6 month+
Must Haves:
* 10+ years experience building production-grade ML systems at scale
* Strong LLM, Generative AI, RAG deployment experience
* Expertise designed systems in cloud environments (AWS, Axure or GCP)
* Hands-on work with Kubernetes, containerizaiton, and scalable inference systems
* Experience designing agentic systems and tool orchestration frameworks
* Ability to implement and govern MCP servers or structured architectures
* Strong python background
Relevant Experience:
* Large-scale distributed ML systems
* LLM and RAG architectures
* Agentic AI frameworks and tool orchestration
* Enterprise platform engineering
Day to Day activities:
* Define reference architecture for LLM, ML, and agent-based systems across products.
* Design high-availability, low-latency inference platforms for global scale.
* Establish reusable platform components for model lifecycle, deployment, and monitoring.
Lead Agentic AI & Tool Ecosystems
* Architect multi-step, reasoning-driven agent systems.
* Design orchestration patterns for tool use, API invocation, and structured function calling.
* Lead implementation and governance of Model Context Protocol (MCP) servers to standardize tool integration and context management.
* Define guardrails, permissions, and audit mechanisms for enterprise-safe AI systems.
Elevate Engineering Standards
* Set best practices for MLOps, CI/CD, observability, and system reliability.
* Embed Responsible AI principles across platform architecture.
* Mentor senior engineers and influence technical direction across teams.
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