Founding ML Engineer: LLM Agents & Time-Series Systems

Stealth Startup; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Stealth Startup is hiring a Founding Machine Learning Engineer to design, train, deploy, and monitor end-to-end ML systems that fuse LLM-powered agents with time-series models. You will shape how agents interact with multimodal data and operate with speed and autonomy in a fast-paced startup.

You will champion production-grade ML, rigorous evaluation, and scalable infrastructure, collaborating with researchers, engineers, and key customers to drive rapid iteration and impact.

Qualifications

• 4–10 years of industry experience shipping production ML systems.
• Hands-on with LLM-powered agents, multi‑step reasoning, tool use, and autonomous workflows.
• Familiar with agent evaluation for reliability, safety, and metrics.

Responsibilities

• Design, train, and deploy production ML systems (LLM-powered agents + time-series models).
• Build and scale agents with multi-step reasoning, tool integration, autonomous workflows, memory, and adaptive strategies.
• Develop evaluation frameworks to ensure reliability, safety, and measurable performance.
• Apply time-series modeling techniques (forecasting, anomaly detection, multimodal data) in real-world scenarios.
• Operate end-to-end from data ingestion to deployment, monitoring, and continuous improvement.
• Stay up-to-date with AI agents, orchestration frameworks, and infrastructure (MCP, A2A).
• Collaborate with researchers, engineers, and lighthouse customers to validate solutions.

Skills

Founding ML Engineer

Production ML systems

LLM-powered agents

Agent evaluation

CI/CD

Observability

Reproducibility

Startup environment

Tools

MCP

A2A

CI/CD pipelines

Job description

Stealth Startup is hiring a Founding Machine Learning Engineer to design, train, deploy, and monitor end-to-end ML systems that fuse LLM-powered agents with time-series models. You will shape how agents interact with multimodal data and operate with speed and autonomy in a fast-paced startup.

You will champion production-grade ML, rigorous evaluation, and scalable infrastructure, collaborating with researchers, engineers, and key customers to drive rapid iteration and impact.