Senior Machine Learning Founding Engineer

Quick Facts

• Role: Senior Machine Learning Founding Engineer

Description

Founding-level responsibility to architect and ship production-grade machine learning systems powering agentic AI workflows. You will own the entire ML lifecycle—from data curation and fine-tuning/training to inference optimization, evaluation, and production monitoring—while building reliable tool-using agents with long-context memory and safety guardrails. Work closely with Product, Engineering, and Research to translate LLM and agentic research into low-latency features for real user workflows.

Responsibilities

• Architect and ship core ML & agent systems for proactive AI agents, task triage engines, and multi-step reasoning workflows

• Take end-to-end ownership of the ML lifecycle: dataset curation, model fine-tuning/training, inference optimization, evaluation, and production monitoring

• Build agentic logic and guardrails for reliable external tool/API execution with persistent contextual memory

• Translate state-of-the-art LLM and agentic research into high-availability software

• Lead design reviews, set high engineering standards, and mentor peers across the ML team

• Partner cross-functionally with Product, Engineering, and Research to ship features that address complex user problems

Benefits

• Founding-member impact on architecture, engineering culture, and product strategy from day one

• Massive financial runway with significant initial investment

• True remote autonomy with flexible working hours and location

• Highly competitive cash and equity compensation

• Meaningful engineering challenges around non-determinism, real-world tool execution, and low-latency agent reasoning

Requirements

• Proven production ML experience architecting, deploying, and maintaining AI/ML systems at scale

• Systems engineering mindset with scalable, robust software design principles

• Understanding of foundation model behavior, failure modes, function calling, and edge-case resolution in live environments

• High ownership and velocity; able to prioritize under production constraints (latency, cost, safety)