Catalyst Labs
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 and generative AI, established tech companies scaling their ML infrastructure, 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 are driving applied intelligence from model optimization to productized AI workflows.
Location & Compensation Union Square, San Francisco – 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. You are an exceptional builder who thrives at the intersection of real‑world features and AI/ML engineering, someone who not only understands how models work, but also how to use them to deliver real, measurable value to end users. This role is central as we scale our GenAI‑native platform for tax document processing, combining the velocity of a startup with the backing of a large multinational firm.
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.
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, 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 (e.g. pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras), cloud providers such as GCP/AWS, container technologies (e.g. Docker, Kubernetes), web application development including Python‑based web servers (e.g. Flask, Django), and database and storage layers (e.g. 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 early‑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 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
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
Sign in to set job alerts for “Machine Learning Engineer” roles. We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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Location & Compensation Union Square, San Francisco – 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. You are an exceptional builder who thrives at the intersection of real‑world features and AI/ML engineering, someone who not only understands how models work, but also how to use them to deliver real, measurable value to end users. This role is central as we scale our GenAI‑native platform for tax document processing, combining the velocity of a startup with the backing of a large multinational firm.
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.
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, 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 (e.g. pandas, scikit‑learn, spaCy, PyTorch, TensorFlow, Keras), cloud providers such as GCP/AWS, container technologies (e.g. Docker, Kubernetes), web application development including Python‑based web servers (e.g. Flask, Django), and database and storage layers (e.g. 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 early‑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 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
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
Sign in to set job alerts for “Machine Learning Engineer” roles. We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr