Sr Machine Learning Engineer, GenAI
Company Overview
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Overview
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 perfect code and user experience, 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
#LI-Hybrid
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 experience
Career Path
Mobility plays an important role for our engineering community. In addition to vertical growth, our teams offer lateral growth opportunities. Whether it’s working on a different tech stack or product, Intuit will help you get to the next step in your career.
- Software Engineer 1 & 2
- Sr. Software Engineer
- Staff Software Engineer
- Sr. Staff Software Engineer
- Principal Software Engineer
- Distinguished Software Engineer
There's so much flexibility in terms of moving not just between teams, but between roles.
Lucy Shen Developer Advocate
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