$203,000 – $284,500
Listed on Intuit’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead machine learning systems from end-to-end—feature pipelines, model training, deployment, and monitoring—for a consumer platform that processes millions in business value. This role suits a seasoned ML engineer who can set technical standards, mentor teammates, and evolve shared infrastructure while directly shipping models that drive measurable impact.
Our summary, not Intuit’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- 7+ years building and deploying production ML systems
- End-to-end ownership of models from data through monitoring
- Batch ML model development including classification, propensity, and uplift modeling
- Models shipped to production with measurable business impact
- Software engineering fundamentals and experience with shared ML libraries or feature stores
- Training and deploying models on modern platforms like Databricks or Spark MLlib
- Python, SQL, and PySpark proficiency
- Navigate ambiguity and deliver business-impacting results
- Communication skills across technical and non-technical teams
Nice to have
- Familiarity with MLOps patterns like CI/CD for models, feature versioning, and drift monitoring
- Experience with agentic development environments