AI Engineer

In this role, you'll be embedded inside a vibrant team of AI scientists and engineers. You'll be expected to help conceive, code, and deploy AI models & generative AI agentic systems at scale using the latest industry tools

Important skills include data pipeline development, prompt engineering, model fine-tuning, retrieval-augmented generation (RAG), and developing robust evaluation metrics.

• Work with AI scientists and engineers to design and implement agentic systems
• Discover data sources, get access to them, import them, clean them up, and prepare them for model training and fine-tuning
• Work with AI scientists to develop and refine data pipelines, building robust systems for fine-tuning, serving, and deploying AI models
• Partner with data scientists and researchers to understand, implement, refine, and design advanced AI and generative model architectures
• Run regular A/B tests, gather data, perform statistical analysis, and draw conclusions on the impact of your AI solutions.
• Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
• Explore new advancements in the generative AI landscape to determine how they might connect with the customer benefits we wish to deliver

• BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
• 6+ years of experience.
• Knowledgeable with AI/ML tools and frameworks (i.e., Python, Hugging Face (Transformers, PEFT), Numpy, Pandas, PyTorch, Tensor Flow, Lang Chain, Llama Index, Spark)
• Deep knowledge of generative AI techniques (i.e., Large Language Models (LLMs), RAG, fine-tuning (LoRA, QLoRA), multi-modal models, and vector databases)
• Understand machine learning principles (training, validation, etc.)
• Knowledge of data query and data processing tools (i.e., SQL)
• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code
• Experience deploying highly scalable software supporting millions or more users
• Experience with GPU acceleration (i.e. CUDA and cuDNN)
• Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
• Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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: