This listing does not state pay. Across 39 open staff machine learning engineer listings that state pay, the middle half runs $227,000 to $277,000 and the median is $255,500.

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How AI is used in this kind of work

Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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Intuit has filed one layoff notice in the last twelve months, covering 162 workers, most recently May 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

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About the job

Intuit is looking for a Staff Software Engineer to build AI/ML systems at the core of our products. You'll design and own shared AI capabilities - model training pipelines, evaluation frameworks, and ML tooling - that power next-generation, AI-driven experiences across personal finance, accounting, and tax. You'll work closely with AI scientists, product, and design, moving from proof-of-concept to production through rapid experimentation and iteration. You'll help build the AI capabilities that every product team depends on - long-term memory systems that let AI experiences retain context and personalize over time, and evaluation frameworks that make model quality and regressions measurable at scale. Besides these core AI capabilities, you'll get to work at the frontier of what AI-native products can be: building agent builder frameworks, embedding AI directly into product experiences, and pushing on cutting-edge agentic AI development.

Responsibilities

Design and own shared AI/ML components, frameworks, and pipelines - spanning model training, evaluation, and fine-tuning - used across multiple product teams

Apply ML fundamentals and LLM techniques (prompting, fine-tuning, RAG) to solve concrete customer problems, then evaluate model performance in production

Build long-term memory and context-retention systems that let AI experiences personalize and stay coherent over time, and evaluation frameworks that make model quality measurable at scale

Prototype and build agent builder frameworks and embedded AI experiences, taking cutting-edge agentic AI concepts from early exploration to product-ready implementations

Drive rapid prototyping and experimentation to move from proof-of-concept to high-accuracy, performant systems

Set best practices for ML tooling and developer workflows; mentor other engineers on AI craft

Stay ahead of emerging GenAI and ML developments and identify where they improve existing products

Collaborate closely with AI scientists, product, and design to navigate ambiguity and ship next-generation AI-driven experiences

Architect and build full-stack, AI-native applications end-to-end, from backend services to production LLM integrations

Set best practices for application architecture; mentor other engineers on software engineering craft

Qualifications

BS, MS, or PhD in Computer Science or equivalent practical experience

8+ years building production AI/ML systems; prior experience leading an engineering effort a plus

Strong CS fundamentals - data structures, algorithms, system design - plus solid ML fundamentals (classification, regression, clustering, neural networks)

Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, Pandas/NumPy)

Practical experience with LLMs: prompt engineering, fine-tuning, and frameworks like LangChain

Experience building or operating agentic systems, agent frameworks, or long-term memory/context architectures for AI applications

Familiarity designing evaluation frameworks or offline/online eval pipelines for measuring model and agent quality

Cloud platform experience for ML workloads (AWS, including SageMaker)

Track record of launching AI integrations in production and evaluating their real-world impact

Strong cross-functional collaboration skills, partnering effectively with data scientists, product managers, and engineers across global teams

Proficiency in one or more full-stack languages (JavaScript, Java) and experience designing scalable services - microservices, relational/NoSQL data stores, Kubernetes

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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 $230,000- $250,000. The expected base pay range for this position is: Mountain View $202,500 - $274,000