Senior Machine Learning Engineer

Join our team as a Senior Machine Learning Engineer, where you will architect and deploy a multi-agent framework for agent assist, internal SOP execution, and secure LLM-powered actions. You will own end-to-end project execution for complex ML initiatives, build and optimize AI-driven concierge chat and agent copilot experiences, and develop systems to detect and manage bad actors. You will also establish best practices for system design, coding standards, and evaluation frameworks for ML/AI systems, while mentoring team members on architectural decisions and modern ML development workflows.

• Architect and deploy a multi-agent framework for agent assist, internal SOP execution, and secure LLM-powered actions.
• Own end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies.
• Build and optimize AI-driven concierge chat and agent copilot experiences that improve automated resolution rates and reduce case handling time.

• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality
• 5+ years of professional experience in machine learning and software engineering, with a track record of shipping production-grade ML services at scale
• Proven ability to write technical design documents and communicate complex ML concepts clearly to non-technical stakeholders across product, design, and CX teams
• Specialized depth in at least one domain: NLP, information retrieval, conversational AI, or advanced statistical modeling, with the ability to ramp quickly on adjacent areas
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality
• Proficiency in Python with the ability to write clean, maintainable, and highly tested production code for ML applications
• Hands-on expertise with large language models, deep learning architectures, and the generative AI ecosystem (LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock), with demonstrated ability to build multi-agent or LLM orchestration systems