AI / ML Engineer

AI / ML Engineer (Python & Ruby)

Location : Mountain View, CA(Hybrid)

EXP : 9+ years

Intuit is seeking a talented and experienced AI / ML Software Engineer to join our innovative engineering team. In this role, you will use both Python and Ruby to build, train, and deploy machine learning models, integrating them into our core applications and services. This position offers a unique opportunity to combine data science principles with robust, scalable software development practices.

Key Responsibilities

• Model Development : Design, develop, and implement machine learning and deep learning models and algorithms using Python and its associated libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Application Integration : Integrate AI / ML models into our production applications and web services, writing high-quality, maintainable, and scalable code primarily in Ruby.
• Data Pipeline Construction : Work with data engineers to build and maintain data processing pipelines for cleaning, manipulating, and preparing data for model training using Python libraries such as Pandas and NumPy.
• Deployment and MLOps : Deploy and manage AI / ML models in production environments, potentially leveraging cloud platforms like AWS, Azure, or Google Cloud.
• Performance Optimization : Monitor and optimize model performance, addressing any issues related to accuracy or efficiency post-deployment.
• Code Quality : Conduct thorough code reviews and adhere to software engineering best practices, ensuring the reliability and quality of both Python and Ruby code.
• Collaboration : Work closely with data scientists, product managers, and other engineering teams to translate business needs into technical requirements and deliver integrated solutions.
• Research and Innovation : Stay current with the latest developments in AI / ML, evaluating new technologies and methodologies to enhance our products.

Required Skills and Qualifications

Python : Proven experience developing and deploying machine learning models and data pipelines. Deep familiarity with key libraries (TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).

Preferred Qualifications