Staff Software Engineer - ML Engineering

Overview

The Intuit Foresight team builds products that accelerate the adoption of new technologies and seed new businesses fueled by technology innovation . You'll be building and prototyping applications to simplify the business of life for 60 million consumers and small businesses. Applications will span multiple business lines, including personal finance, small business accounting, and tax.

You will thrive on ambiguity and experimentation while working closely with AI Scientists building the next generation of AI algorithms. You will be part of a small but high velocity team where team members frequently wear multiple hats as they build new products. The position involves close collaboration with our product, AI and design teams, as well as product teams in business units.

Responsibilities

Responsibilities

• Responsible for design of common components/frameworks/models that assist in building AI native apps, Fullstack LLM apps.
• Own end to end development of frameworks/models/ ML pipelines that fit use cases by working with the consuming teams and dependencies.
• Being able to navigate through ambiguity, lead with clarity and PoC
• Rapid prototyping, experimentation and iterations to build/own high accuracy/performant frameworks/models.
• Self organized, explore new shifts in GenAI/AI and look at possible application/improvements in the existing use cases.
  
  

Qualifications

• BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience with 8+ years of experience in building/designing AI/ML applications. Atleast 1 year of experience working as a lead for a team with AI/ML engineers.
• Well versed in building with Python, PyTorch, Numpy, Pandas, TensorFlow
• Machine learning fundamentals for supervised, unsupervised & reinforcement learning (i.e. classification, regression, clustering, neural networks) and experience in building production grade models with precision/recall.
• Understand and apply machine learning principles (training, weights, validation, testing, error, cost) optimizing for accuracy/feedback. Should establish and own metrics/optimization.
• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
• Experience with integrating applications and platforms with cloud technologies (e.g: AWS Sagemaker)
• Understanding of LLM, LangChain, CustomGPTs, Prompt Management, and ability to fine-tune base models to build efficient production-grade LLM apps.
  
  

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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.