Applied AI / ML Engineer

Position Overview

Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. Our client—a San Francisco–based startup—is building a GenAI-native platform that automates complex tax document processing, turning dense tax documents into structured, usable data with near-human accuracy. In this role, you will join a team of proven builders, working at the intersection of real-world features and AI/ML engineering to scale a platform that combines startup velocity with enterprise resources.

Key Responsibilities

• Build and scale the ML and product infrastructure that powers intelligent tax document processing at production scale.
• Design and optimize inference systems, dataset pipelines, and specific logic to improve accuracy, speed, and quality as the platform expands.
• Collaborate closely with accountants and tax domain experts to understand workflows, pain points, and quality thresholds, translating insights into productized ML systems.
• Integrate inference pipelines into a seamless, end-to-end experience that transforms how tax professionals process and interpret documents.
• Develop expert systems that encode institutional tax knowledge into scalable, maintainable software components.
• Drive experiments, measure outcomes, and iterate rapidly on core ML metrics.
• Collaborate cross-functionally with product, engineering, and leadership to shape technical direction and influence product vision.

Required Qualifications

• 4+ years of experience in machine learning/AI engineering with proven end-to-end ownership of ML-powered products.
• Strong track record of building systems that create direct user value, beyond research prototypes or internal tooling.
• Proven ability to work with large, complex datasets optimizing for accuracy, scalability, and reliability.
• Proficiency in Python and popular ML libraries (e.g. pandas, scikit-learn, spaCy, PyTorch, TensorFlow, Keras); experienced with cloud providers (GCP/AWS), container technologies (Docker, Kubernetes), and web development frameworks (Flask, Django).
• Experience deploying or integrating LLMs, LLM APIs, agents, and prompt engineering into production systems.
• Hands-on familiarity with ML infrastructure and data workflows, including document understanding, OCR, or applied NLP.
• Exposure to financial or tax-related data environments and startup or 0-to-1 product experience.
• Exceptional problem-solving ability, growth trajectory, and strong communication skills to engage with domain experts.

Benefits & Perks

• Location: Union Square, San Francisco
• Work Type: Full Time, 5 days a week On-Site
• Compensation: above market base + bonus + equity
• Visa: Sponsorship available for candidates with demonstrated brilliance and expertise