Catalyst Labs
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Applied AI / ML Engineer
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Catalyst Labs . About Us
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. We partner directly with AI‑first startups, established tech companies scaling their ML infrastructure, and enterprise innovation teams integrating AI into traditional domains. We collaborate with founders, CTOs, and Heads of AI to drive applied intelligence from model optimization to productized workflows. Client
The role is with a San Francisco‑based startup building a GenAI‑native platform that automates finance and tax document processing. The platform turns complex tax documents into structured data with near‑human precision and over 99 % accuracy on income lines. 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 qualified candidates. What We Are Looking For
5+ years of experience building and scaling commercial machine learning systems, especially in document understanding and extraction. A builder who thrives at the intersection of real‑world features and AI/ML engineering, delivering measurable user value. Roles & 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 logic to improve accuracy, speed, and quality as we expand to millions of documents. Collaborate closely with accountants and tax domain experts to understand workflows 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. Qualifications
Core Experience
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. Experience with large, complex datasets, optimizing for accuracy, scalability, and reliability. Proficiency in Python and ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras); cloud and container technologies (GCP/AWS, Docker, Kubernetes); web development (Flask/Django); and database/storage layers (PostgreSQL, SQL, S3/GCS). Experience deploying or integrating LLMs, LLM APIs, agents, and prompt engineering into production systems. Experience in document understanding, OCR, or applied NLP. Exposure to financial or tax‑related data environments. Startup or early‑product experience. Soft Skills
Exceptional problem‑solving ability, curiosity, and product intuition. Strong communication skills, engaging directly with domain experts and translating complex needs into technical solutions. Growth trajectory demonstrated through promotions or increasing scope of responsibility. Other Roles in Applied AI / ML in the US
Applied AI / ML engineer focusing on LLMs and Knowledge Graphs:
https://www.careers-page.com/catalyst-labs
#J-18808-Ljbffr
Applied AI / ML Engineer
role at
Catalyst Labs . About Us
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. We partner directly with AI‑first startups, established tech companies scaling their ML infrastructure, and enterprise innovation teams integrating AI into traditional domains. We collaborate with founders, CTOs, and Heads of AI to drive applied intelligence from model optimization to productized workflows. Client
The role is with a San Francisco‑based startup building a GenAI‑native platform that automates finance and tax document processing. The platform turns complex tax documents into structured data with near‑human precision and over 99 % accuracy on income lines. 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 qualified candidates. What We Are Looking For
5+ years of experience building and scaling commercial machine learning systems, especially in document understanding and extraction. A builder who thrives at the intersection of real‑world features and AI/ML engineering, delivering measurable user value. Roles & 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 logic to improve accuracy, speed, and quality as we expand to millions of documents. Collaborate closely with accountants and tax domain experts to understand workflows 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. Qualifications
Core Experience
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. Experience with large, complex datasets, optimizing for accuracy, scalability, and reliability. Proficiency in Python and ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras); cloud and container technologies (GCP/AWS, Docker, Kubernetes); web development (Flask/Django); and database/storage layers (PostgreSQL, SQL, S3/GCS). Experience deploying or integrating LLMs, LLM APIs, agents, and prompt engineering into production systems. Experience in document understanding, OCR, or applied NLP. Exposure to financial or tax‑related data environments. Startup or early‑product experience. Soft Skills
Exceptional problem‑solving ability, curiosity, and product intuition. Strong communication skills, engaging directly with domain experts and translating complex needs into technical solutions. Growth trajectory demonstrated through promotions or increasing scope of responsibility. Other Roles in Applied AI / ML in the US
Applied AI / ML engineer focusing on LLMs and Knowledge Graphs:
https://www.careers-page.com/catalyst-labs
#J-18808-Ljbffr