Jobs
Benefits & Perks
•Equity
•Healthcare
•Equity
•Healthcare
Required Skills
Machine Learning
Python
Java
Scala
TensorFlow
PyTorch
Intuit is looking for a highly motivated and experienced Principal Machine Learning Engineer to join the Monetization & Personalization team. Our mission is to drive measurable business and customer impact by building intelligent, personalized, and revenue-optimizing experiences across Intuit’s ecosystem of financial products.
In this role, you will lead the design and deployment of advanced Machine Learning and AI systems that power personalized recommendations, dynamic pricing, offer optimization, customer segmentation, experimentation, and lifecycle monetization. You will work closely with Data Scientists, Product Managers, and Engineers to translate customer intent and behavioral signals into scalable, production-ready ML solutions that improve engagement, conversion, retention, and lifetime value.
Responsibilities
-
Lead the design, implementation, and deployment of end-to-end ML systems that drive personalization and monetization use cases such as recommendations, next-best-action, offer targeting, pricing optimization, churn prediction, and customer lifetime value modeling.
-
Architect scalable ML platforms and pipelines for ingesting high-volume behavioral, transactional, and contextual data; building robust training, evaluation, and experimentation frameworks; and deploying models that deliver quantifiable revenue and customer outcomes.
-
Embed Intuit’s domain expertise into models using techniques such as feature engineering, representation learning, fine-tuning, prompt engineering, and hybrid rule-based + ML approaches where appropriate.
-
Accelerate innovation through rapid experimentation, building prototypes to validate hypotheses and scaling successful approaches into reliable, production-grade systems.
-
Partner closely with Product, Data Science, and Design teams to align ML solutions with monetization strategy, customer journeys, and personalization goals.
-
Define and drive a multi-year technical roadmap for personalization and monetization ML, ensuring the team stays ahead of industry trends in AI, experimentation, and decision intelligence.
-
Influence and contribute to Intuit’s ML platform architecture, including model serving, feature stores, experimentation platforms, and real-time decisioning systems.
-
Champion technical excellence, operational rigor, and responsible AI practices, including fairness, transparency, and measurement of customer impact.
-
Mentor and grow junior engineers, setting a high bar for engineering quality, ML rigor, and system design.
Qualifications
-
MS or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field; equivalent industry experience will be considered.
-
10+ years of experience building and deploying Machine Learning solutions in production, with demonstrated impact on business or customer outcomes.
-
Strong Computer Science fundamentals, including data structures, algorithms, distributed systems, and performance optimization.
-
Expertise in Python, Java, or Scala, and ML frameworks such as Tensor Flow or Py Torch.
-
Solid understanding of ML techniques relevant to personalization and monetization, including:
-
Recommendation systems
-
Classification and regression models
-
Customer segmentation and propensity modeling
-
Experimentation, A/B testing, and causal inference (nice to have)
-
Experience designing highly scalable ML systems on cloud platforms (AWS, GCP, or Azure) that serve millions of users with low latency and high reliability.
-
Strong communication and collaboration skills, with the ability to clearly explain complex technical concepts to both technical and non-technical stakeholders.
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:
Total Views
0
Apply Clicks
0
Mock Applicants
0
Scraps
0
Similar Jobs

Applied Scientist
Microsoft · India, Karnataka, Bangalore
AI Experimental Systems Research Scientist (Causal Learning & Adaptive Experimentation)
3M · 2 Locations

AI Data Scientist
Booz Allen Hamilton · Fort Meade, MD

Data Scientist
Booz Allen Hamilton · Falls Church, VA

Applied Scientist, Quantum Computing
Amazon · Pasadena, CA, USA
About Intuit
Reviews
3.6
9 reviews
Work Life Balance
3.8
Compensation
3.2
Culture
3.1
Career
3.7
Management
3.0
65%
Recommend to a Friend
Pros
Flexible schedule and work independence
Good benefits and 401k match
Supportive teammates and collaboration
Cons
Management issues and favoritism
High pressure and quotas
Poor communication and politics
Salary Ranges
91 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist
5 reports
$150,492
total / year
Base
$115,763
Stock
-
Bonus
-
$138,970
$163,540
Interview Experience
7 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 86%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment/Technical Screen
3
Live Coding Interview
4
Case Study/Technical Assessment
5
Behavioral Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Case Study
System Design
News & Buzz
National Pension Service Increases Holdings in Intuit Inc. $INTU - MarketBeat
Source: MarketBeat
News
·
4w ago
TD Waterhouse Canada Inc. Sells 3,745 Shares of Intuit Inc. $INTU - MarketBeat
Source: MarketBeat
News
·
4w ago
Marketers on Fire: Intuit CMO Talks New Platform Positioning, AI’s Role in Marketing and QuickBooks’ Latest Campaign - Chief Marketer
Source: Chief Marketer
News
·
5w ago
Intuit Stock Is Down 24% Already In 2026. Time to Buy? - The Motley Fool
Source: The Motley Fool
News
·
5w ago
