Responsibilities

We are looking for an exceptional Associate Data Scientist to join our growing AI team. In this role, you will design, build, deploy, and improve ML/LLM-powered services and features that power intelligent automation and AI-driven product experiences across the Workato platform. You will work closely with our Engineering, Product, and Design teams to define and track product metrics and evaluation strategies, design customer-facing experiments and dive deep to provide actionable insights.This role is ideal for someone who combines strong ML/LLM intuition, software engineering skills and a practical mindset for shipping reliable, scalable AI systems.

• 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.

Requirements

Qualifications / Experience / Technical Skills

• 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 Snowflake.