Catalyst Labs
Applied AI / ML Engineer
Join Catalyst Labs as an
Applied AI / ML Engineer .
Location:
Union Square, San Francisco Work type:
Full Time, On Site Compensation:
above market base + bonus + equity Visa:
sponsorship available for qualified candidates
What We Are Looking For 5+ years building and scaling commercial machine‑learning systems, especially in document understanding and extraction. Proven ability to translate model work into real, measurable value, strong Python and ML infrastructure skills, and experience with LLMs, agents, and prompt engineering.
Roles & Responsibilities
Build and scale the ML and product infrastructure powering 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 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.
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, not only research prototypes or internal tooling.
Demonstrated ability to work with large, complex datasets, optimizing for accuracy, scalability, and reliability.
Proficient in Python and popular ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras) and cloud providers (GCP, AWS).
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 early‑product experience is a plus.
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.
Referrals increase your chances of interviewing at Catalyst Labs.
#J-18808-Ljbffr
Applied AI / ML Engineer .
Location:
Union Square, San Francisco Work type:
Full Time, On Site Compensation:
above market base + bonus + equity Visa:
sponsorship available for qualified candidates
What We Are Looking For 5+ years building and scaling commercial machine‑learning systems, especially in document understanding and extraction. Proven ability to translate model work into real, measurable value, strong Python and ML infrastructure skills, and experience with LLMs, agents, and prompt engineering.
Roles & Responsibilities
Build and scale the ML and product infrastructure powering 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 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.
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, not only research prototypes or internal tooling.
Demonstrated ability to work with large, complex datasets, optimizing for accuracy, scalability, and reliability.
Proficient in Python and popular ML libraries (pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras) and cloud providers (GCP, AWS).
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 early‑product experience is a plus.
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.
Referrals increase your chances of interviewing at Catalyst Labs.
#J-18808-Ljbffr