Come join the VEP (Virtual Expert Platform) AI team as a Staff Machine Learning Engineer!

The Horizon AI team is dedicated to building Autonomous Operations for Intuit's Expert Network. Our mission is to deliver AI-native solutions across forecasting, planning, optimization, and routing to drive clarity and efficiency in decision-making.

In this role, you will be a technical lead embedded within a team of AI scientists and engineers. You will move beyond standard predictive modeling to tackle some of the hardest problems in enterprise operations: large-scale optimization and complex resource allocation. You will be responsible for designing and deploying systems that determine how thousands of experts are hired, scheduled, and assigned to millions of customers.

You will take ownership of critical engines like the demand forecasting, capacity planning, schedule and task assignment systems, moving them from heuristic prototypes to robust, production-grade solvers using techniques like Mixed-Integer Programming (MIP) and Constraint Satisfaction.

Responsibilities

• Optimization Engine Development: Architect and implement enterprise-scale optimization engines for hiring/supply decisions and shift generation/activity assignment. Translate business constraints into mathematical formulations using Mixed-Integer Linear Programming (MILP) or Constraint Satisfaction.

• Productionize AI & Operations: Build and scale machine learning models and optimization solvers using modern frameworks. Develop reliable pipelines and microservices that can handle millions of variables and decision points.

• Advanced Forecasting: Collaborate with scientists to implement driver-based and attribute-driven forecasting models to predict demand (volume, handle-times) and supply availability, handling challenges like sparsity and hierarchical constraints.

• System Modernization: Lead the transition from legacy heuristic models to robust, self-healing AI systems. Enforce high standards for code coverage, unit testing, and observability (OpEx) to ensure system stability.

• Cross-Functional Leadership: Partner with product managers, operations leaders, and data scientists to define the roadmap for Autonomous Operations. Translate complex operational needs into technical AI solutions.

Innovation: Explore and implement emerging technologies, including Reinforcement Learning (RL) for real-time decision-making and agentic automation workflows.

Qualifications

• Education: BS, MS, or PhD degree in Computer Science, Operations Research, Industrial Engineering, or a related field.

• Experience: 6+ years of industry experience in applied machine learning, AI engineering, or software engineering.

• Core Engineering: Strong proficiency in Python and software engineering fundamentals (data structures, algorithms, version control, CI/CD). Experience deploying highly scalable software supporting millions of users.

Cloud & Infrastructure: Experience integrating applications with cloud technologies (i.e., AWS, GCP) and containerization (Docker/Kubernetes).

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: 

San Diego, California: $184,500 - $250,000

Bay Area, California: $197,000 - $266,500