Lead the end-to-end architectural design for machine learning applications, ensuring all solutions are highly-available, low latency, scalable, robust, and reusable.
Partner closely with the Data Science team to ensure models are production-ready and aligned with application requirements.
Collaborate with the Data Engineering Architect to synchronize data pipelines, storage solutions, and feature delivery.
Work with the broader community of organization architects to reach consensus and ensure consistency across technology standards.
Design "Full-Stack" solutions that encompass both complex back-end ML logic and intuitive front-end delivery layers.
Actively contribute to the codebase by developing core Python application components and integration logic.
Manage technical delivery by adhering to the team roadmap and ensuring all solutions are feasible to deliver by designated due dates.

7+ years of experience in software engineering or systems architecture, with a significant focus on Machine Learning systems.
Expert-level proficiency in Python and its associated ecosystem for application development.
Proven experience designing and implementing full-stack architectures (Back-end APIs and Front-end frameworks).
Strong knowledge of distributed systems and scalable infrastructure (e.g., Docker, Kubernetes, AWS).
Experience managing the lifecycle of production-grade machine learning applications.
Effective communicator and collaborator, capable of aligning technical strategies between data scientists, engineers, and stakeholders.
Self-disciplined, motivated, and a problem-solver mindset.

Solution Architect, Machine Learning Applications

Key skills