Job description

Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive, code, and deploy AI science models at scale using the latest industry tools. As a Senior engineer, you deliver durable solutions and independently manage complex or multiple features, beginning to influence team processes. What You'll Do You own the technical outcomes of your projects and their operational excellence, shaping architectural decisions and ensuring your code is suited for scaling and rapid iteration. Responsibilities Technical Skills & Engineering • 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. Execution & Delivery • Provide accurate estimates for projects, considering technical risks, team capacity, and the quality of AI-generated code. • Eliminate systematic roadblocks through cross-functional influence, maintaining quality standards throughout the development cycle. • Take full responsibility for successfully delivering major features or projects, managing risks and keeping stakeholders informed. • Run and interpret A/B tests and statistical analyses to determine model and feature impact. Customer Impact • Collect customer feedback, usage, and product data to reach a deep understanding of customer workflows, using data to influence product direction. • Partner with Product and Design to shape priorities based on real customer behavior and business goals. • Define success at the outset, track adoption and impact, and drive post-launch iterations. Collaboration & Team Growth • Share feedback with team members on best practices, helping teammates work more effectively and take on larger work. • Resolve ambiguities and provide clarity to team members, documenting what works so standards travel across the team. • Work cross-functionally with product managers, data/AI scientists, and product engineers. Qualifications • BS, MS, or PhD in Computer Science or related field, or equivalent practical experience. • 5+ years of experience. • Knowledgeable with data science/AI tools and frameworks (Python, Scikit-learn, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark). • Solid understanding of ML techniques (classification, regression, clustering) and ML principles. • Computer science fundamentals: data structures, algorithms, performance complexity, and computer architecture. • Software engineering fundamentals: version control (Git/GitHub); ability to write production-ready code. • Experience deploying highly scalable software supporting millions or more users; GPU acceleration (CUDA, cuDNN) and cloud (AWS, GCP) experience. • Strong oral and written communication skills; able to explain complex material to non-technical audiences. 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: Mountain View $171,000 - $231,500 San Diego, CA $154,000- $208,500

Requirements

Must-haves

Senior Machine Learning Engineer
You own the technical outcomes of your projects and their operational excellence, shaping architectural decisions and ensuring your code is suited for scaling and rapid iteration.
Technical Skills & Engineering
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.
Execution & Delivery
Provide accurate estimates for projects, considering technical risks, team capacity, and the quality of AI-generated code.
Eliminate systematic roadblocks through cross-functional influence, maintaining quality standards throughout the development cycle.
Take full responsibility for successfully delivering major features or projects, managing risks and keeping stakeholders informed.
Run and interpret A/B tests and statistical analyses to determine model and feature impact.
Customer Impact
Collect customer feedback, usage, and product data to reach a deep understanding of customer workflows, using data to influence product direction.
Partner with Product and Design to shape priorities based on real customer behavior and business goals.
Define success at the outset, track adoption and impact, and drive post-launch iterations.
Collaboration & Team Growth
Share feedback with team members on best practices, helping teammates work more effectively and take on larger work.
Resolve ambiguities and provide clarity to team members, documenting what works so standards travel across the team.
Work cross-functionally with product managers, data/AI scientists, and product engineers.
BS, MS, or PhD in Computer Science or related field, or equivalent practical experience.
5+ years of experience.
Knowledgeable with data science/AI tools and frameworks (Python, Scikit-learn, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark).

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaimlpythonawsgcp

Platform: career-feeds
Effort: medium