refresh

トレンド企業

トレンド企業

採用

求人Intuit

Principal Machine Learning Engineer Mountain View, California

Intuit

Principal Machine Learning Engineer Mountain View, California

Intuit

mountain view

·

On-site

·

Full-time

·

2mo ago

報酬

$254,500 - $344,000

福利厚生

Healthcare

401(k)

Equity

Flexible Hours

必須スキル

Machine Learning

Python

Java

Scala

TensorFlow

PyTorch

Data structures

Algorithms

Distributed systems

Leadership

Intuit is seeking a highly motivated and experienced Principal Machine Learning Engineer to join our Mid Market AI team. In this influential role, you will lead the design, development, and deployment of end-to-end AI/ML solutions that power the next generation of intelligent features across Intuit’s financial products. You will shape strategy, drive innovation, and scale impactful solutions that deliver measurable value to our customers.

Responsibilities

  • Technical Leadership: Define and own AI strategy and ML platform architecture, setting a multi-year technical roadmap.
  • End-to-End ML Systems: Lead the full lifecycle of ML solutions—from data curation and model training to robust deployment and monitoring in production.
  • Cutting-Edge AI Applications: Apply state-of-the-art technologies such as Large Language Models (LLMs) and Multimodal Language Models to solve complex business
  • Innovation & Prototyping: Accelerate experimentation by building rapid prototypes and scaling successful solutions to production.
  • Mentorship: Provide technical guidance to junior engineers, foster a culture of technical excellence, and champion operational rigor.
  • Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to deliver solutions that drive customer success.

Qualifications

  • Master's or Ph.D. in Computer Science or a related field with a focus on AI/ML or equivalent experience.
  • 10+ years of experience developing and deploying production-level ML.
  • Expertise in programming languages such as Python, Java, or Scala.
  • Proficiency with modern ML frameworks (Tensor Flow, Py Torch).
  • Strong foundation in computer science fundamentals (data structures, algorithms, distributed systems).
  • Proven communication and leadership skills to influence technical direction and engage both technical and non-technical stakeholders.

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 1 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: Bay Area California: $254,500 - 344,000ReferencesVisible links1. https://www.intuit.com/careers/benefits/full-time-employees/

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Intuitについて

Intuit

Intuit

Public

Intuit provides financial software solutions to empower individuals and businesses.

10,001+

従業員数

Mountain View

本社所在地

$140B

企業価値

レビュー

2.6

10件のレビュー

ワークライフバランス

3.5

報酬

3.8

企業文化

3.2

キャリア

3.4

経営陣

2.8

35%

友人に勧める

良い点

Good benefits and compensation

Supportive team and leadership

Flexible schedule and work-life balance

改善点

Inadequate training and software support

Poor management and lack of support

High expectations and micromanagement

給与レンジ

91件のデータ

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Business Data Analyst

2件のレポート

$123,000

年収総額

基本給

$116,528

ストック

-

ボーナス

-

$123,000

$123,000

面接体験

7件の面接

難易度

3.0

/ 5

期間

14-28週間

内定率

14%

体験

ポジティブ 14%

普通 86%

ネガティブ 0%

面接プロセス

1

Application Review

2

Online Assessment/Technical Screen

3

Live Coding Interview

4

Case Study/Technical Assessment

5

Behavioral Interview

6

Offer

よくある質問

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Case Study

System Design