Intuit is looking to solve the problem of delivering end-to-end AI solutions that span multiple domains and products, influencing the strategic direction of machine learning and AI across the company.
Requirements
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- Expert in ML lifecycle management, feature engineering, and large-scale model deployment.
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- Deep hands-on experience with modern ML frameworks and distributed systems (TensorFlow, PyTorch, Spark, Ray, Kubernetes, MLflow, etc.).
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- Experience leading cross-functional initiatives spanning multiple product or platform
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- Strong background in software engineering fundamentals: algorithms, distributed systems, data pipelines, and performance optimization.
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- Familiarity with LLMs, GenAI, and applied responsible AI practices is a strong plus.
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- Proven track record of architecting and delivering production-scale ML systems that impact millions of users.
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- Experience with cloud-native and open-source technologies (e.g., AWS, GCP)
Responsibilities
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- Lead the architectural design of complex, cross-cutting ML systems and data platforms that serve multiple Intuit products.
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- Drive the adoption of AI-native design principles, ensuring that systems are built for adaptability, observability, and secure customer data usage.
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- Build and scale end-to-end ML solutions using cloud-native and open-source technologies (e.g., AWS, GCP, TensorFlow, PyTorch, Ray, Spark).
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- Define engineering standards, model governance, and MLOps best practices across teams for training, deployment, monitoring, and continuous improvement.
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- Evaluate and integrate transformative technologies such as foundation models, retrieval-augmented generation (RAG), and LLM fine-tuning pipelines to accelerate product innovation.
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- Resolve deeply complex issues across domains, often requiring novel solutions or architectural evolution for long-term scalability.
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- Deliver within large-scale strategic initiatives, identifying systemic architectural gaps and leading their resolution across multiple teams.
Other
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- BS, MS, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
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- 8+ years of experience in software or ML engineering, with at least 3+ years at Staff level or equivalent leadership scope.
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- Excellent communication and influence skills, capable of aligning technical direction with organizational strategy.
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- Ability to mentor and develop Staff and Senior MLEs, building a strong culture of learning, quality, and execution excellence.
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- Ability to drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
