AI Engineer - Machine Learning

AI Engineer – Machine Learning

• 🌍 U.S. Citizenship, Must be a US Citizen
• 🕒 Full-Time - This role is a remote full-time position within the United States.
• ✈️This role may require up to 10-20% travel, including periodic travel to our offices for team collaboration, planning activities, and in-person meetings."

• About the Role
• We are hiring two AI/ML Engineers for an early-stage, high-growth AI infrastructure company. Our team is building an enterprise-grade platform and we need highly curious, hard-working self-starters.
• You will own the design and delivery of complex, multi-service AI architectures involving agent orchestration, secure workflows and real-world operational constraints.

• What You Will Do
• Own the architecture, design, and implementation of full AI/ML systems, including: Multi-service, distributed system architecture, workflow and agent orchestration.
• Proven experience designing and deploying complex agentic systems using LLMs.
• Hands-on design with multi-agent orchestration, routing, and tool orchestration.
• Building products and harness around AI models, harness engineering. Product Engineering.
• Your work goes far beyond prompts or app-level features. You will architect platforms and sustainable AI infrastructure.
• You will build real, production agents—not prototypes relying solely on framework abstractions.
• End-to-End AI Infrastructure with Python, AWS, Typescript. MCP servers to connect to agentic services with response API, Pydantic outputs, tool calling, guardrails, LLM validation framework, etc..

• Desired Qualifications
• 4+ years working professionally as a Machine Learning Engineer or Data Scientist.
• 1-2+ years building and deploying Agentic, ML / LLM-powered systems in production environments.
• Degree in Computer Science, Computer Engineering, Data Science or similar.
• Experience developing, deploying and productionizing supervised and unsupervised machine learning models.
• Proficient with: Python, Claude, OpenAI, MCP, Agentic Workflows, tool calling, Evaluation frameworks, cache management, knowledge graphs, agentic harness, eval harness, model validation framework, LLM.
• 📌Has built agentic systems or multi-agent setups, LangChain, LangGraph, Strands, ADK, or any orchestration framework.
• Work across cloud environments (AWS, Azure, GCP)

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