Sr Machine Learning Engineer, GenAI

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.
Petah Tikva, Israel
Machine Learning
Senior Software Engineer
Hybrid
5,000+ Employees
AI · Finance

Description For Sr Machine Learning Engineer, GenAI

Intuit is seeking a Sr Machine Learning Engineer for their Generative AI group. This role involves designing and building systems to improve Generative AI inference, quantization, optimization, finetuning, and evaluation. The ideal candidate will work cross-functionally with product managers, data scientists, and engineers to implement and refine Generative AI models. Key responsibilities include exploring state-of-the-art technologies, building end-to-end pipelines, and effectively communicating results. The role requires expertise in LLM technologies, machine learning frameworks, cloud technologies (particularly AWS), and software container technology. Experience with designing Generative AI architectures and strong foundations in computer science, mathematics, and software engineering are essential. This position offers the opportunity to work on cutting-edge technology and contribute to innovative products that impact millions of customers worldwide.

Last updated a month ago

Responsibilities For Sr Machine Learning Engineer, GenAI

  • Design and build systems for Generative AI inference, quantization, optimization, finetuning, and evaluation
  • Work cross-functionally with product managers, data scientists, and engineers
  • Effectively communicate results to peers and leaders
  • Explore state-of-the-art technologies and apply them to deliver customer benefits
  • Interact with various data sources and build end-to-end pipelines

Requirements For Sr Machine Learning Engineer, GenAI

Python
Kubernetes
  • 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 and principles
  • Data query and data processing tools or systems
  • Distributed computing systems and related technologies
  • Software engineering fundamentals
  • Computer science fundamentals
  • Mathematics fundamentals: linear algebra, calculus, probability
  • BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience

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