Senior Staff Software Engineer , Innovation Research

Job Overview

The Intuit Futures Organization is a team dedicated to pushing boundaries and driving innovation within the company. The team achieves this through a variety of means, such as experimentation, extensive research, POC and MVP initiatives.  Through these methods, the team aims to develop and incubate emerging technologies, user experiences, and capabilities. By constantly exploring new ideas, the Intuit Futures team identifies and develops solutions that have the potential to be transformative to our customers, products, and business. The team’s work ensures that Intuit remains at the forefront of innovation and is able to continue delivering valuable products and services that meet the evolving needs of our customers.

As a Senior Staff AI Engineer within the Intuit Futures organization, you will play a pivotal role in driving innovation and developing cutting-edge products and technologies that benefit both our internal and external customers.

Responsibilities

• AI Solutions Design and Development: Architect, design, and implement AI applications using GenAI and neural networks to solve complex business and customer problems
• Model Training and Optimization: Develop, train, and optimize machine learning models and neural networks, ensuring high performance and scalability.
• Data Analysis and Preprocessing: Perform data analysis and preprocessing to prepare datasets for training AI models. Ensure data quality and integrity.
• Documentation and Reporting: Document the model development process, including methodologies, algorithms used, and performance metrics. Report findings and results to stakeholders.
• MVP Development and Handoff: Develop POCs and MVPs and facilitate handover to other business units. Provide training, documentation, and support to ensure smooth graduation and full integration.

Qualifications

Experience: Minimum of 10 years of experience in AI engineering.

Education: Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.

Technical Skills:

• AI Technologies: Practical experience with AI frameworks / libraries (e.g., TensorFlow, PyTorch).
• GenAI: Proficiency in Generative AI techniques and applications.
• Machine Learning: Proficiency in machine learning algorithms, model training, and deployment.
• Neural Networks: Solid understanding of neural network architectures and techniques.
• Data Engineering: Experience in data preprocessing, cleaning, and feature engineering 
• Python Coding: Proficiency in Python for end-to-end pipelines, data training, and model serving.
• Cloud Computing: Comprehensive experience with AWS and cloud-based AI/ML services.
• AI DevOps: Experience with CI/CD pipelines, Docker, and automation for AI/ML models.
• AI Ethics and Compliance: Knowledge of AI ethics, data privacy, and compliance standards.

Soft Skills:

• Creativity and Innovation: Ability to think outside the box and generate innovative solutions.
• Results-Oriented: Strong focus on efficient, proactive task completion and goal achievement.
• Adaptability: Comfort with rapid task-switching and adaptable to changing priorities.
• Problem-Solving: Excellent at diagnosing and resolving complex technical challenges.
• Team Player: Collaborative team player committed to collective success.
• Communication: Proficient in explaining AI concepts to business stakeholders.
• Leadership: Capability to inspire and guide a team, providing mentorship and fostering a culture of continuous improvement.