Catalyst Labs
Overview
Applied AI / ML Engineer role at Catalyst Labs. Location: Union Square, San Francisco. Work type: Full Time, On-Site. Compensation: above market base + bonus + equity. Visa: sponsorship available for candidates with demonstrated brilliance and expertise.
About Us Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We partner directly with AI-first startups building products powered by LLMs, generative AI, intelligent automations; established tech companies scaling ML infrastructure; and enterprise innovation teams integrating AI into finance, healthcare, and logistics. We collaborate with founders, CTOs, and Heads of AI to align technical expertise with growth trajectories. Our client is a San Francisco based startup building a GenAI-native platform that automates tax document processing.
What We Are Looking For Were seeking an Applied AI / ML Engineer with 5+ years of experience building and scaling commercial machine learning systems in ownership roles, especially with document understanding and extraction. You are an exceptional builder who thrives at the intersection of real world features and AI/ML engineering, delivering real, measurable value to end users. This role scales GenAI-native platform for tax document processing.
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 with accountants and tax domain experts to understand workflows, pain points, and quality thresholds; translate insights into productized ML systems.
Integrate inference pipelines into an end-to-end experience for tax professionals.
Develop expert systems that encode institutional tax knowledge into scalable software components.
Drive experiments, measure outcomes, and iterate on core ML metrics.
Collaborate with product, engineering, and leadership to shape technical direction and product vision.
Qualifications Core Experience
4+ years of experience in machine learning / AI engineering with end-to-end ownership of ML-powered products.
Proven ability to build systems that create direct user value.
Experience with large, complex datasets; strong understanding of building, measuring, and iterating on ML systems and ML-powered products.
Proficiency with Python and ML libraries (pandas, scikit-learn, spaCy, PyTorch, TensorFlow, Keras); cloud providers (GCP/AWS); container tech (Docker, Kubernetes); web frameworks (Flask, Django); and databases/storage (Postgres, SQL, S3/GCS).
Experience deploying or integrating LLMs, LLM APIs, Agents and prompt engineering into production.
Strong Python and ML infrastructure/data workflow experience.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax-related data environments.
Startup or early-stage product experience.
Soft Skills
Exceptional problem-solving ability, curiosity, and product intuition.
Strong communication skills with ability to engage domain experts and translate needs into technical solutions.
Growth trajectory demonstrated through promotions or increasing scope of responsibility.
Other roles in Applied AI / ML in the US, check them out here:
Applied AI / ML engineer focusing on LLMs, and Knowledge Graphs: https://www.careers-page.com/catalyst-labs
Location: Union Square, San Francisco
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About Us Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We partner directly with AI-first startups building products powered by LLMs, generative AI, intelligent automations; established tech companies scaling ML infrastructure; and enterprise innovation teams integrating AI into finance, healthcare, and logistics. We collaborate with founders, CTOs, and Heads of AI to align technical expertise with growth trajectories. Our client is a San Francisco based startup building a GenAI-native platform that automates tax document processing.
What We Are Looking For Were seeking an Applied AI / ML Engineer with 5+ years of experience building and scaling commercial machine learning systems in ownership roles, especially with document understanding and extraction. You are an exceptional builder who thrives at the intersection of real world features and AI/ML engineering, delivering real, measurable value to end users. This role scales GenAI-native platform for tax document processing.
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 with accountants and tax domain experts to understand workflows, pain points, and quality thresholds; translate insights into productized ML systems.
Integrate inference pipelines into an end-to-end experience for tax professionals.
Develop expert systems that encode institutional tax knowledge into scalable software components.
Drive experiments, measure outcomes, and iterate on core ML metrics.
Collaborate with product, engineering, and leadership to shape technical direction and product vision.
Qualifications Core Experience
4+ years of experience in machine learning / AI engineering with end-to-end ownership of ML-powered products.
Proven ability to build systems that create direct user value.
Experience with large, complex datasets; strong understanding of building, measuring, and iterating on ML systems and ML-powered products.
Proficiency with Python and ML libraries (pandas, scikit-learn, spaCy, PyTorch, TensorFlow, Keras); cloud providers (GCP/AWS); container tech (Docker, Kubernetes); web frameworks (Flask, Django); and databases/storage (Postgres, SQL, S3/GCS).
Experience deploying or integrating LLMs, LLM APIs, Agents and prompt engineering into production.
Strong Python and ML infrastructure/data workflow experience.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax-related data environments.
Startup or early-stage product experience.
Soft Skills
Exceptional problem-solving ability, curiosity, and product intuition.
Strong communication skills with ability to engage domain experts and translate needs into technical solutions.
Growth trajectory demonstrated through promotions or increasing scope of responsibility.
Other roles in Applied AI / ML in the US, check them out here:
Applied AI / ML engineer focusing on LLMs, and Knowledge Graphs: https://www.careers-page.com/catalyst-labs
Location: Union Square, San Francisco
#J-18808-Ljbffr