Join the innovative Generative AI group, to help build the next generation of awesome products and experiences using cutting-edge technology.
If you love having stretch goals, challenges, and making customers incredibly happy while fostering your obsessive need for elegant, state of the art technology which drives impact and creates awesome user experiences, this is the job for you.
You will collaborate with many teams in Intuit and contribute to many components in different business units. We love engineers who lead the change, communicate with customers, and deliver the most beautiful and intuitive applications.
In this role, you’ll:
Be part of a vibrant team of Data Scientists and ML Engineers
Be expected to help code, optimize, and deploy GenAI models at scale, using the latest industry tools and techniques
Help automate, deliver, monitor, and improve GenAI solutions
Responsibilities
Design and build systems, which improve Generative AI inference, quantization, optimization, finetuning, and evaluation
Work cross-functionally with product managers, data scientists, and engineers to understand, implement, refine, and design Generative AI models
Effectively communicate results to peers and leaders
Explore the state-of-the-art technologies and apply them to deliver customer benefits.
Interact with a variety of data sources, working closely with peers and partners to refine features from the underlying data and build end-to-end pipelines
Qualifications
LLM experience: LangChain, vLLM, HuggingFace toolkit
Machine Learning oriented languages, tools, and frameworks: Spark, Python
Cloud technologies, in particular AWS, and Software container technology: Docker, Kubernetes, KubeFlow / MLflow
Experience with designing and developing Generative AI architectures
Machine learning techniques (classification, regression, and clustering) and principles (training, validation, and testing)
Data query and data processing tools or systems: relational, NoSQL, stream processing
Distributed computing systems and related technologies: Spark, Hive
Software engineering fundamentals: version control systems (Git, Github) and workflows, and ability to write production-ready code
Computer science fundamentals: data structures, algorithms, performance, complexity, and implications of computer architecture on software performance (I/O and memory tuning)
Mathematics fundamentals: linear algebra, calculus, probability
BS, MS, or PhD degree in Computer Science or related field, or equivalent practical
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.
