Founding Machine Learning Engineer (MLE) specializing in Agent Development and Time-Series Modeling

Join us as a Founding Machine Learning Engineer (MLE) specializing in Agent Development and Time-Series Modeling. You will have a pivotal role in creating robust production systems that merge LLM-powered agents with advanced time-series models.

The Role

This position goes beyond traditional research; you will design, train, deploy, and monitor comprehensive ML systems, driving projects from prototype to production swiftly and independently. You'll be instrumental in defining interactions between agents and multimodal numerical data—a frontier rich with potential.

Key Responsibilities

• Design, train, and deploy cutting-edge production ML systems focusing on LLM-powered agents and time-series models.
• Engineer and expand LLM-powered agents, incorporating advanced functionalities such as multi-step reasoning, tool integration, autonomous workflows, and memory management.
• Develop and enhance evaluation frameworks, ensuring agents are reliable, safe, and perform measurably.
• Utilize and advance time-series modeling techniques in practical scenarios, including forecasting and anomaly detection.
• Manage the entire ML lifecycle: from data ingestion and preprocessing to deployment and ongoing enhancement.
• Keep abreast of innovations in AI agents, orchestration frameworks, and related infrastructures.
• Collaborate with researchers, engineers, and key customers to validate solutions and expedite iterations.

What We're Seeking

• 4-10 years of proven industry experience as an ML Engineer, Research Engineer, or Applied Scientist, with a successful track record of deploying production ML systems.
• Hands-on expertise with LLM-powered agents, including multi-step reasoning and autonomous workflows.
• Solid understanding of agent evaluation methodologies focused on reliability and safety.
• Familiarity with modern agent infrastructures and frameworks.
• Fluency in ML engineering best practices, including reproducibility and observability.
• Comfort in a fast-paced startup environment, able to adapt and prioritize effectively.

Preferred Qualifications

• Experience in training custom neural networks tailored for time-series or multimodal data.
• A solid foundation in time-series modeling techniques and methodologies.
• Publications or contributions to the open-source ML/AI community.

Location & Sponsorship

• Location: San Francisco Bay Area, CA (in-person)
• Visa Sponsorship: H1-B, O1