Responsibilities

Role Overview

We are looking for an exceptional Applied AI Researcher (OCR) to join our growing AI team and work on OCR-focused product capabilities.

In this role, you will design, build, deploy, and improve machine learning systems for intelligent document understanding. The project involves extracting information from complex document layouts, including tables, embedded images, multi-column text, forms, and other non-trivial visual elements, while maintaining high accuracy and robustness in production environments.

This role is ideal for someone with strong analytical thinking, solid computer vision expertise, and hands-on experience building ML systems for real-world document understanding tasks. Experience with OCR pipelines and LLM-based post-processing or document understanding systems is highly desirable.

What You’ll Do

• Build and improve AI services using LLMs and custom machine learning models for production use cases.
• Design, develop, and operate ML/LLM systems end-to-end, from prototyping to deployment and monitoring.
• Write high-quality Python code that is testable, maintainable, and efficient.
• Improve validation, observability, and performance monitoring for ML services (quality, latency, reliability, cost).
• Partner cross-functionally with product managers, platform engineers, and other stakeholders to ship AI-powered product capabilities.
• Evaluate and improve existing implementations by identifying bottlenecks, bugs, and opportunities for optimization.
• Design controlled experiments to test the features for our AI-based products and perform deep analysis from the results to find actionable insights
• Contribute to technical design and code reviews, helping raise engineering quality across the team.
• Experiment and iterate on model behavior, prompting, retrieval, tool use, or orchestration strategies to improve user outcomes.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent practical experience
• 3+ years of experience in Machine Learning Engineering, Data Science, or a similar role.
• Strong Python programming skills.
• Hands-on experience with CV and/or LLM-based systems.
• Experience deploying and operating ML services in production.
• Strong understanding of software engineering fundamentals (testing, code quality, debugging, version control).
• Ability to work collaboratively in a fast-moving environment and drive projects with ownership.

Preferred Qualifications

• Experience with tool-use agents or workflow-aware AI systems.
• Experience building AI products in enterprise SaaS environments.
• Experience with A/B testing and statistical significance techniques.
• Experience with LLMOps/MLOps tooling and practices (monitoring, evaluation pipelines, model rollout, CI/CD).
• Experience working with modern data warehouses such as Amazon Redshift or Snowflake.

Why Join Workato

Workato gives an opportunity to work on real-world, high-impact AI problems in enterprise orchestration and automation. We believe in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. 

All full-time regular employees will be eligible for the following benefits:

• Workato Stock Options at one of Silicon Valley’s fastest growing startups
• Health benefits: Medical, dental, vision for yourself and covered dependents/domestic partners
• Pre-tax benefits: Medical and dependent care flexible spending accounts, health savings account, and commuter benefits
• Company-paid life insurance and short/long-term disability insurance
• Paid maternity/parental leave benefits for new parents
• Enhanced employee assistance program for mental wellness

(REQ ID: 2706)