ML Engineer 2

Apply software development practices to design, implement, and support individual software projects. Work on problems of moderate scope and complexity where analysis of situations or data requires a review of multiple factors of the overall product and service. Review product requirements and architecture to understand and implement software projects. Develop highly scalable, secure and efficient software that support critical functions of Intuit’s engineering operations and/or Intuit’s leading commercial software products. Working with Senior and Staff Engineers, collect and analyze requirements from Product Managers. In an Agile/SCRUM environment, develop, define and write code to implement algorithms to develop software application features in compliance with business requirements. Write unit test case and test code for validity. Perform bug fixes by analyzing discrepancies that are found by the Quality Assurance team. Deploy software code for automated testing. Develop code for review/correction by senior level engineers, and produce production-ready code. Design, code, test, and maintain assigned software deliverables, and represent the customer perspective during software development activities. Contribute to the improvement of product development methods and tools.

Responsibilities

Use GenAI (LLMs/Agents) to develop rapid prototypes and production-ready solutions. Architect data pipelines (ingestion, transformation, persistence) and workflow pipelines (Kubeflow) to develop scalable solutions.

Education Requirements: MS, or PhD in Computer Science, Machine Learning, or Data Engineering Position requires: Skills: 4+ years of industry experience (Example) * Object oriented programming - algorithmic problem solving for building modular and maintainable software systems * Systems architecture - Design patterns to design scalable modular systems * Cloud infrastructure - Experience working with cloud platforms for development like AWS (s3/ Sagemaker/ EC2 instance) * Container orchestration platforms - Experience with containerization and container orchestration platforms for deployment, scaling and management of applications and machine learning (ML) workflows (ex: Kubernetes) * Data engineering - Experience in processing, transforming and managing raw data to support analytics and machine learning workflows * Canonical knowledge of ML basics - Strong understanding of ML concepts and lifecycle processes for ML-based solutions (training, evaluation, validation, etc.) * Applied ML - Practical experience in building end-to-end M/ Deep leaning application (data labelling, data processing, training, testing and deploying) * LLMs & GenAI applications - Experience in developing application backed by LLMs (GenAI) like RAG/ agentic workflows * Programming and data tools (ex: scientific libraries) - Experience using Python (Pandas, Numpy, etc.) and related technologies for data processing, visualization and ML frameworks Footer

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: Mountain View $140,500 - $190,000 New York $136,000- $184,000 San Diego, CA $127,000- $172,000