Catalyst Labs
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Applied AI / ML Engineer
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Catalyst Labs
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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 stand out as an agency that is deeply embedded in our clients' recruitment operations. We partner directly with AI‑first startups building products powered by LLMs, generative AI, and intelligent automations; established tech companies scaling their ML infrastructure, recommendation systems, and data platforms; and enterprise innovation teams integrating AI into traditional domains such as finance, healthcare, and logistics.
We collaborate directly with founders, CTOs, and Heads of AI who drive the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem‑solving mindset, and long‑term growth trajectory in the evolving world of intelligent systems.
Our Client A San Francisco‑based startup building a GenAI‑native platform that automates complex tax challenges. Their system turns dense tax documents into structured data in minutes, achieving over 99% accuracy on income lines and streamlining workflows across Excel and API integrations. Backed by seasoned founders and AI leaders from top‑tier tech companies, they apply GenAI to redefine how financial data is understood.
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.
What We Are Looking For We’re seeking an Applied AI / ML Engineer with 5+ years of experience building and scaling commercial machine learning systems, especially with document understanding and extraction. You thrive at the intersection of real‑world features and AI/ML engineering, understanding how models work and how to use them to deliver measurable value to end users.
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 specific logic to improve accuracy, speed, and quality as we expand to millions of documents.
Collaborate closely with accountants and tax domain experts to deeply 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.
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, not just research prototypes or internal tooling.
Demonstrated ability to work with large, complex datasets, optimizing for accuracy, scalability, and reliability. Strong fundamental understanding of how to build, measure, and iterate on ML systems and ML‑powered enterprise or consumer products.
Comfortable with Python and popular ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras), cloud providers such as GCP/AWS, container technologies (Docker, Kubernetes), web application development including Python‑based web servers (Flask, Django), and database and storage layers (Postgres, SQL, S3/GCS).
Experience deploying or integrating LLMs, LLM APIs, Agents and prompt engineering into production systems.
Strong Python proficiency and hands‑on familiarity with ML infrastructure and data workflows.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax‑related data environments.
Startup or product experience.
Soft Skills
Exceptional problem‑solving ability, curiosity, and product intuition.
Strong communication skills with the ability to engage directly with domain experts and translate complex needs into technical solutions.
Growth trajectory demonstrated through promotions or increasing scope of responsibility.
Other Roles Applied AI / ML engineer focusing on LLMs, and Knowledge Graphs: https://www.careers-page.com/catalyst-labs
Seniority Level Not Applicable
Employment Type Full‑time
Job Function Engineering and Information Technology
Industries Business Consulting and Services
Referrals increase your chances of interviewing at Catalyst Labs by 2x
Get notified about new Machine Learning Engineer jobs in
San Francisco, CA .
#J-18808-Ljbffr
Applied AI / ML Engineer
role at
Catalyst Labs
Get AI-powered advice on this job and more exclusive features.
About Us Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that is deeply embedded in our clients' recruitment operations. We partner directly with AI‑first startups building products powered by LLMs, generative AI, and intelligent automations; established tech companies scaling their ML infrastructure, recommendation systems, and data platforms; and enterprise innovation teams integrating AI into traditional domains such as finance, healthcare, and logistics.
We collaborate directly with founders, CTOs, and Heads of AI who drive the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem‑solving mindset, and long‑term growth trajectory in the evolving world of intelligent systems.
Our Client A San Francisco‑based startup building a GenAI‑native platform that automates complex tax challenges. Their system turns dense tax documents into structured data in minutes, achieving over 99% accuracy on income lines and streamlining workflows across Excel and API integrations. Backed by seasoned founders and AI leaders from top‑tier tech companies, they apply GenAI to redefine how financial data is understood.
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.
What We Are Looking For We’re seeking an Applied AI / ML Engineer with 5+ years of experience building and scaling commercial machine learning systems, especially with document understanding and extraction. You thrive at the intersection of real‑world features and AI/ML engineering, understanding how models work and how to use them to deliver measurable value to end users.
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 specific logic to improve accuracy, speed, and quality as we expand to millions of documents.
Collaborate closely with accountants and tax domain experts to deeply 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.
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, not just research prototypes or internal tooling.
Demonstrated ability to work with large, complex datasets, optimizing for accuracy, scalability, and reliability. Strong fundamental understanding of how to build, measure, and iterate on ML systems and ML‑powered enterprise or consumer products.
Comfortable with Python and popular ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras), cloud providers such as GCP/AWS, container technologies (Docker, Kubernetes), web application development including Python‑based web servers (Flask, Django), and database and storage layers (Postgres, SQL, S3/GCS).
Experience deploying or integrating LLMs, LLM APIs, Agents and prompt engineering into production systems.
Strong Python proficiency and hands‑on familiarity with ML infrastructure and data workflows.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax‑related data environments.
Startup or product experience.
Soft Skills
Exceptional problem‑solving ability, curiosity, and product intuition.
Strong communication skills with the ability to engage directly with domain experts and translate complex needs into technical solutions.
Growth trajectory demonstrated through promotions or increasing scope of responsibility.
Other Roles Applied AI / ML engineer focusing on LLMs, and Knowledge Graphs: https://www.careers-page.com/catalyst-labs
Seniority Level Not Applicable
Employment Type Full‑time
Job Function Engineering and Information Technology
Industries Business Consulting and Services
Referrals increase your chances of interviewing at Catalyst Labs by 2x
Get notified about new Machine Learning Engineer jobs in
San Francisco, CA .
#J-18808-Ljbffr