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Distinguished Engineer - Intuit Intelligence, ML & AI

Mountain View, California, United States

Actively hiring, first seen by us 2 days ago
Pay
$316,000–427,000/year · BaseAnnual period assumed — pay source
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: Mountain View $316,000 - $427,000
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Work setting
Not stated
Employment
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What you’ll work on

Full posting

We are seeking a Distinguished Engineer to shape the technical and scientific direction of Intuit Intelligence.

You will connect research, model development, agent engineering, and production delivery across multiple organizations.

  • Define long-term AI and ML strategy tied to customer needs and production limits

  • Architect and build agents that reason, retrieve information, use tools, and complete tasks

  • Establish reusable approaches for agent orchestration, memory, and failure recovery

  • Guide model selection, training, and inference using evidence and quality, latency, cost tradeoffs

  • Build evaluation systems for model quality, task completion, robustness, and safety

From the employer’s posting
We are seeking a Distinguished Engineer to shape the technical and scientific direction of Intuit Intelligence. You will combine deep expertise in AI science and machine learning with hands-on experience building agents that solve meaningful customer problems.
You will connect research, model development, agent engineering, and production delivery across multiple organizations. Your work will establish reusable foundations for intelligent products and demonstrate where emerging AI capabilities can create durable business value. At least 40% of your time will be devoted to technical contributions, including experiments, prototypes, agent development, evaluation, and production problem-solving.
Define the long-term AI and ML strategy, connecting scientific advances to customer needs, product opportunities, and production constraints.
Architect and build agents that reason over context, retrieve information, use tools, coordinate workflows, and complete tasks with appropriate human oversight.
Establish reusable approaches for agent orchestration, context and memory management, capability integration, and recovery from failures.
Guide model selection, adaptation, training, and inference decisions using scientific evidence and explicit tradeoffs in quality, latency, and cost.
Build evaluation systems that measure model quality, end-to-end task completion, robustness, safety, and customer value.

What you’ll bring

All qualifications

Core experience

  • Deep expertise in AI science and machine learning
  • Hands-on experience building agents that solve customer problems
Qualification wording
combine deep expertise in AI science and machine learning with hands-on experience building agents
hands-on experience building agents that solve meaningful customer problems
Apply at Intuit

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$316K–$427K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 6 and day 69.

At Intuit, jobs usually come down by about day 22.

From 4,423 similar postings that came down, and 64 of Intuit’s. Coming down is not always a hire.

Intuit is hiring

59 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring is picking up
  • Takes jobs down quickly
Hiring record

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Your next step

Complete your application on jobs.intuit.com. The employer’s form will show what is required.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About the role

We are seeking a Distinguished Engineer to shape the technical and scientific direction of Intuit Intelligence. You will combine deep expertise in AI science and machine learning with hands-on experience building agents that solve meaningful customer problems.

You will connect research, model development, agent engineering, and production delivery across multiple organizations. Your work will establish reusable foundations for intelligent products and demonstrate where emerging AI capabilities can create durable business value. At least 40% of your time will be devoted to technical contributions, including experiments, prototypes, agent development, evaluation, and production problem-solving.


Responsibilities

What you’ll do

  • Define the long-term AI and ML strategy, connecting scientific advances to customer needs, product opportunities, and production constraints.

  • Architect and build agents that reason over context, retrieve information, use tools, coordinate workflows, and complete tasks with appropriate human oversight.

  • Establish reusable approaches for agent orchestration, context and memory management, capability integration, and recovery from failures.

  • Guide model selection, adaptation, training, and inference decisions using scientific evidence and explicit tradeoffs in quality, latency, and cost.

  • Build evaluation systems that measure model quality, end-to-end task completion, robustness, safety, and customer value.

  • Establish production practices for monitoring, experimentation, model and agent lifecycle management, and continuous improvement.

  • Address difficult challenges in grounding, uncertainty, generalization, permissions, privacy, and reliable execution.

  • Develop firsthand judgment through research and implementation, advancing promising ideas from experiments into validated product capabilities.

  • Partner with engineering, product, design, data science, and security leaders; mentor senior technical talent and model responsible agent-driven development.


Qualifications

What you’ll bring

  • Deep expertise in AI science and ML, including statistical learning, deep learning, experimental design, and rigorous evaluation.

  • Demonstrated experience building and operating production AI systems and agents that perform consequential workflows.

  • Strong understanding of foundation models, retrieval, tool use, agent orchestration, and techniques for adapting models to domain needs.

  • The ability to distinguish improvements in model behavior from improvements in system reliability and customer outcomes.

  • A record of translating research into scalable products and reusable technical capabilities.

  • Strong software and systems engineering judgment, with the ability to influence technical direction across organizations.

  • The ability to explain scientific uncertainty and technical tradeoffs clearly to executive and technical audiences.

What success looks like

AI and agents complete customer tasks with measurable quality and reliability. Scientific advances translate into adopted product capabilities, reusable foundations accelerate delivery, and teams improve customer outcomes while managing operational cost and risk.


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:
Mountain View $316,000 - $427,000
Source details

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Pay
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: Mountain View $316,000 - $427,000
Location & working pattern

Mountain View, California, United States

Working pattern and location restrictions need checking in the full posting.

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