Founding Machine Learning Engineer

Founding ML Engineer

Location: San Francisco, CA Company Stage: Early-Stage (YC-backed, Profitable, High-Growth) Office Type: Onsite Salary: $150,000 – $300,000 + Equity (0.10% – 0.50%)

This fast-growing, venture-backed startup is building the core infrastructure layer that enables AI agents to access, understand, and act on real-time internet data. Instead of traditional search workflows designed for humans, the platform provides APIs that allow AI systems to retrieve high-fidelity, structured data directly from source systems.

The company has achieved strong early traction—scaling to millions in ARR within its first year—and is already serving enterprise customers. Backed by leading investors including Y Combinator and top-tier venture firms, the team is now focused on pushing the boundaries of applied machine learning to power the next generation of AI-native data systems.

What You Will Do

Own the end-to-end development of core ML systems—from research and modeling to production deployment

Design and train models for information retrieval, entity resolution, classification, and structured data extraction

Build systems that transform messy, multilingual web-scale data into structured, queryable intelligence

Develop embedding models, ranking systems, and retrieval pipelines for high-precision search and matching

Apply transformer architectures and modern NLP techniques to real-world data problems

Leverage LLMs for tasks such as extraction, classification, and data enrichment at scale

Continuously evaluate and improve model performance using rigorous experimentation and metrics

Work closely with engineering and product teams to integrate ML systems into production APIs

Ideal Background

3+ years of experience building and shipping production ML systems, particularly in NLP, information retrieval, or entity resolution

Strong hands-on experience with Python and PyTorch

Deep understanding of transformer architectures, including training and fine-tuning encoder models

Experience building retrieval systems, classifiers, or embedding-based systems

Familiarity with representation learning techniques (e.g., contrastive learning, metric learning)

Experience applying LLMs to structured data problems (e.g., extraction, classification, generation)

Strong problem-solving skills with the ability to work on ambiguous, large-scale data challenges

High ownership mindset with a strong bias toward execution in fast-paced environments

Preferred

Experience with entity resolution or record linkage at scale

Background in multilingual or cross-lingual NLP

Experience building taxonomies, ontologies, or knowledge systems

Familiarity with distributed training on GPU clusters

Experience scaling LLM inference pipelines in production

Research publications or open-source contributions in NLP/IR

Compensation and Benefits

Base salary: $150K – $300K

Equity: 0.10% – 0.50% (founding-level ownership)

Visa sponsorship available

Opportunity to join at an early stage with strong product-market fit and rapid growth

High ownership role with direct impact on core product and company trajectory

Work alongside experienced founders and top-tier investors

This role is ideal for ML engineers who want to operate at the frontier of applied NLP and retrieval—owning core intelligence systems that power how AI agents interact with real-world data at scale.