Senior ML Engineer: Architect & Deliver Scalable AI

Intuit Inc.; United States; In loco; USD 150.000 - 230.000; Tempo pieno

Vantaggi offerti da questo lavoro

Bonus eligibility

Equity rewards

Descrizione del lavoro

Intuit Inc. seeks a Senior Machine Learning Engineer to conceive, code, and deploy AI models at scale using modern industry tools. You will own the technical outcomes of projects and influence architectural decisions.

You will design ML features, run A/B tests, collaborate with data scientists, product and design, and ensure production-ready, scalable software. The role emphasizes measurable impact and clear communication across stakeholders.

Competenze

• BS, MS, or PhD in Computer Science or related field.
• 5+ years of experience in ML engineering.
• Knowledgeable with data science/AI tools and frameworks (Python, Scikit-learn, TensorFlow, Keras, Spark).

Mansioni

• Lead technical design of complex ML features and systems, make sound architectural decisions, and provide effective documentation.
• Create durable technical examples and drive best-practices adoption, including testing and observability, documenting reusable patterns for work built alongside AI agents.
• Solve complex, ambiguous technical bugs that may require reaching outside your team for knowledge and resources.
• Stay fluent in modern AI-assisted development practices; lead technology and design evaluation and adoption.
• Design and refine ML features and pipelines with data scientists across the ML lifecycle.

Conoscenze

Python

Scikit-learn

NLTK

NumPy

Pandas

TensorFlow

Keras

R

Spark

Machine Learning

Git

CUDA

cuDNN

AWS

GCP

Communication skills

Formazione

BS, MS, or PhD in Computer Science or related field

Strumenti

GitHub

Docker

Descrizione del lavoro

Intuit Inc. seeks a Senior Machine Learning Engineer to conceive, code, and deploy AI models at scale using modern industry tools. You will own the technical outcomes of projects and influence architectural decisions.

You will design ML features, run A/B tests, collaborate with data scientists, product and design, and ensure production-ready, scalable software. The role emphasizes measurable impact and clear communication across stakeholders.