Catalyst Labs
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Applied AI / ML Engineer
role at
Catalyst Labs
Catalyst Labs is a leading talent agency specialized in Applied AI, Machine Learning, and Data Science.
Location:
Union Square, San Francisco Work type:
Full Time, 5 days a week On-Site. Compensation:
above market base + bonus + equity Visa:
sponsorship available.
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.
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 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.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax-related data environments.
Startup or 01 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.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or veteran status.
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Applied AI / ML Engineer
role at
Catalyst Labs
Catalyst Labs is a leading talent agency specialized in Applied AI, Machine Learning, and Data Science.
Location:
Union Square, San Francisco Work type:
Full Time, 5 days a week On-Site. Compensation:
above market base + bonus + equity Visa:
sponsorship available.
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.
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 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.
Experience in document understanding, OCR, or applied NLP.
Exposure to financial or tax-related data environments.
Startup or 01 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.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or veteran status.
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