Highlight
Summary
About the Role
About You
- 5+ years of experience in software development, with at least 2+ years focused on building and scaling machine learning platforms or large-scale distributed systems.
- Strong proficiency in one or more programming languages commonly used in ML (e.g., Python, Java, Go, Scala).
- Extensive experience with AWS cloud services or other cloud platforms (GCP, Azure) and containerization technologies (Docker, Kubernetes).
- Solid understanding of machine learning concepts, MLOps principles, and the lifecycle of ML models.
- Demonstrated ability to design, build, and operate highly scalable and reliable services.
- Excellent problem-solving skills, with the ability to break down complex problems into manageable solutions.
- Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse teams.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- Experience with specific ML platform components such as feature stores (e.g., Feast), model registries (e.g., MLflow), or model serving frameworks (e.g., Seldon Core, TensorFlow Serving).
- Experience with Generative AI models, frameworks, and deployment (e.g., LLMs, diffusion models, fine-tuning, prompt engineering).
- Contributions to open-source projects related to ML platforms or MLOps.
Intuit is a global technology platform that helps our customers and communities overcome their most important financial challenges. Serving millions of customers worldwide with TurboTax, QuickBooks, Credit Karma and Mailchimp, we believe that everyone should have the opportunity to prosper and we work tirelessly to find new, innovative ways to deliver on this belief. We encourage conversations on this page and will not delete comments that follow our terms of use. In order to keep this a safe community, the below posts may be removed: Repeated posts of the same content, spam or posts from fake accounts or profiles, offensive language or material, threats to others in the community, posts deliberately aimed to have a negative effect on the community or conversations.