Senior ML Engineer: Scale, Deploy & Optimize Models

Intuit Inc.; Mountain View (CA); On-site; USD 171,000 - 232,000; Full time

Job summary

Intuit Inc. is seeking a Data Scientist / Machine Learning Engineer to architect, code, optimize, and deploy ML models at scale using modern tools.

You will automate, monitor, and improve ML solutions, collaborating with product managers, data scientists, and engineers to deliver robust, scalable ML systems. Requirements include strong software development, systems engineering, and data wrangling skills, plus familiarity with ML frameworks like TensorFlow and Keras, and cloud technologies such

Qualifications

• BS, MS, or PhD in Computer Science or related field, or equivalent practical experience.
• Languages: Scala, Java, Python.
• CS fundamentals: data structures, algorithms, performance, and architectures.
• Software engineering: Git and production-ready code, workflows.
• ML/Data Science tools: SQL, SkLearn, NLTK, NumPy, Pandas, TensorFlow, Keras.
• ML techniques: classification, regression, clustering; training/validation/testing.
• Data processing: Spark, Hive, Flink; cloud: AWS SageMaker.
• DevOps: CI/CD; containers: Docker, Kubernetes.

Responsibilities

• Design and build systems to improve ML scalability, usability, and performance.
• Work cross functionally with product managers, data scientists, and engineers to understand, implement, refine, and design ML and other algorithms.
• Effectively communicate results to peers and leaders.
• Explore state-of-the-art technologies and apply them to deliver customer benefits.
• Interact with data sources, refine features from data, and build end-to-end pipelines.

Skills

Scala

Java

Python

Education

BS/MS/PhD in Computer Science or related field

Tools

Git

GitHub

TensorFlow

Keras

NumPy

Pandas

Scikit-learn

NLTK

Docker

Kubernetes

Spark

Hive

Flink

AWS SageMaker

Job description

Intuit Inc. is seeking a Data Scientist / Machine Learning Engineer to architect, code, optimize, and deploy ML models at scale using modern tools.

You will automate, monitor, and improve ML solutions, collaborating with product managers, data scientists, and engineers to deliver robust, scalable ML systems. Requirements include strong software development, systems engineering, and data wrangling skills, plus familiarity with ML frameworks like TensorFlow and Keras, and cloud technologies such