ML Engineer 2

About the role

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 supports 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 cases and test code for validity. Perform bug fixes by analyzing discrepancies 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.

Requirements

Education

• MS or PhD in Computer Science, Machine Learning, or Data Engineering

Skills

• 4+ years of industry experience
• 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 (e.g., 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 machine/deep learning applications (data labeling, data processing, training, testing, and deploying)
• LLMs & GenAI applications – Experience in developing applications backed by LLMs (GenAI) like RAG/agentic workflows
• Programming and data tools (e.g., scientific libraries) – Experience using Python (Pandas, NumPy, etc.) and related technologies for data processing, visualization, and ML frameworks

Pay

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

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. Intuit provides a competitive compensation package with a strong pay-for-performance rewards approach, including a cash bonus, equity rewards, and benefits.