Applied AI / ML Engineer

Job Description

Job Description

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 thats deeply embedded in our clients recruitment operations. We partner directly with : AI-first startups building products powered by LLMs, generative AI, 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 in those themes who are driving 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

Is a San Francisco based startup building a GenAI-native platform that automates one of the most complex, time-consuming challenges in finance and Tax and turning dense tax documents into structured, usable data in minutes. Their system processes everything from K-1s and K-3s to intricate footnotes with near-human precision, achieving over 99% accuracy on income lines and streamlining workflows across Excel and API integrations.

They serve some of the most sophisticated players in private wealth, and asset management, helping them move faster and make better decisions in an industry where accuracy and speed define competitiveness. Backed by seasoned founders and AI leaders from top-tier tech companies like facebook and salesforce, this team combines product craftsmanship with cutting-edge machine learning to bring intelligence to a domain that has long resisted automation.

Recently acquired by a global technology leader, the company now operates with the mindset, pace, and creative autonomy of a startup but with the stability, benefits, and resources of an established enterprise. Youll be joining a team of proven builders whove scaled products to acquisition, engineered systems that power billions of data points, and are now applying GenAI to redefine how financial data is understood, structured, and acted upon.

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

Were seeking an Applied AI / ML Engineer with 5+ years of experience building and scaling commercial machine learning systems in meaningful 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, 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 they scale their GenAI-native platform for tax document processing, combining the velocity of a startup with the backing of resources and reach of a large multi national 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 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.