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.

In an Agile/SCRUM environment, collaborate with Senior and Staff Engineers to collect and analyze requirements from Product Managers, develop and define code to implement algorithms, write unit test cases, perform bug fixes, and deploy software for automated testing. Produce production-ready code and 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.
• Design, code, test, and maintain assigned software deliverables, representing the customer perspective during development.

Qualifications

Education

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

Experience & Skills

• 4+ years of industry experience in software development.
• Object-oriented programming: Algorithmic problem-solving for building modular and maintainable software systems.
• Systems architecture: Design patterns to create scalable modular systems.
• Cloud infrastructure: Experience with cloud platforms like AWS (S3, SageMaker, EC2).
• Container orchestration: Experience with Kubernetes for deployment, scaling, and management of applications and ML workflows.
• Data engineering: Processing, transforming, and managing raw data to support analytics and ML workflows.
• Machine Learning basics: Strong understanding of ML concepts and lifecycle processes (training, evaluation, validation).
• Applied ML: Practical experience building end-to-end ML/deep learning applications (data labeling, processing, training, testing, deploying).
• LLMs & GenAI applications: Experience developing applications backed by LLMs (e.g., RAG, agentic workflows).
• Programming & data tools: Proficiency in Python (Pandas, NumPy) and related technologies for data processing, visualization, and ML frameworks.

Pay

Expected base pay range for this position:

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

Pay is based on job-related knowledge, skills, experience, and work location. Intuit conducts regular comparisons across categories of ethnicity and gender to drive ongoing fair pay.

Benefits

Intuit provides a competitive compensation package including cash bonus, equity rewards, and benefits (see Intuit Careers | Benefits).