Founding AI

ESSENTIAL RESPONSIBILITIES

Own the full ML research lifecycle: problem formulation, experimentation, model training, evaluation, optimization, and deployment. Design and improve state-of-the-art Computer Vision and Document AI models for parsing and understanding unstructured enterprise data. Lead architectural improvements to vision models and VLM-based document understanding systems. Build scalable data pipelines and evaluation frameworks to continuously measure and improve performance. Transition research prototypes into reliable, production-grade systems in collaboration with engineering. Establish best practices for experimentation, reproducibility, benchmarking, and iteration. Work directly with founders to shape product direction and long-term technical strategy. Contribute to research credibility through publications, benchmarks, or open contributions when appropriate.

QUALIFICATIONS

Education Master’s or PhD in Computer Science, Computer Vision, Document AI, or a closely related field from a top-tier institution. Strong academic research background with multiple publications in relevant areas preferred. Experience Up to 6 years of experience post–Master’s or PhD. Proven experience owning end-to-end ML research initiatives. Experience in a 0-to-1 startup environment with high ambiguity and rapid iteration. Background at a leading research lab (e.g., DeepMind, FAIR, Microsoft Research, OpenAI, Anthropic) strongly preferred. Technical Skills Deep expertise in Computer Vision, Document AI, multimodal learning, or related domains. Experience building or significantly improving model architectures. Experience working with smaller foundation models (e.g., 3B–7B parameter range). Strong Python proficiency and familiarity with modern ML frameworks. Experience training and deploying models for parsing and understanding unstructured data. Hands-on experience building evaluation pipelines and integrating models into production systems. Soft Skills Comfortable moving between theory, experimentation, and production deployment. Strong product intuition and ability to prioritize research with business impact. High ownership mindset and bias toward action. Willingness to work in person and commit to the intensity of an early-stage company.

IDEAL CANDIDATE PROFILE

Has built or materially improved document layout models or vision-language systems. Demonstrates architectural depth beyond fine-tuning existing models. Thrives in fast-paced environments with minimal process. Motivated by building category-defining infrastructure from the ground up.

WORK ENVIRONMENT

In-person role based in San Francisco, CA. Fast-moving startup environment with high ownership and accountability. Flexible hours with potential for extended work periods during high-demand cycles.

COMPENSATION & BENEFITS

Competitive base salary: $200K–$300K Meaningful equity ownership: 0.1%–1% Visa sponsorship availab