Lead ML Engineer

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Requirements:

• 7+ years of experience building and maintaining large-scale production ML systems, with a focus on performance, scalability, and reliability.
• Proven experience as the owner or significant contributor to products used by tens of thousands of customers, with the ability to make complex design decisions.
• Expertise in machine learning algorithms, productionizing ML models, and scaling systems to handle large data volumes.
• Strong problem-solving skills with creative approaches to overcoming technical challenges.
• Experience leading technical discussions, driving decisions, and setting technical standards for a team.
• Excellent written and verbal communication skills, with the ability to articulate complex technical topics to both technical and non-technical stakeholders.
• Familiarity with modern orchestration platforms (Kubernetes, containerization, microservice design) and distributed systems.
• Ability to identify, define, and segment complex research problems and drive innovative solutions that align with business and technical goals.

Responsibilities:

• Lead large-scale ML projects and products from inception to production, overseeing the entire lifecycle from design and implementation to deployment and maintenance.
• Make key architectural decisions to ensure solutions are scalable, efficient, and maintainable while balancing business and technical constraints.
• Drive collaboration across ML and engineering teams to ensure product success, influencing technical discussions and decisions at all levels.
• Design and implement state-of-the-art machine learning pipelines and models that impact millions of users and generate real business value.
• Set technical standards and lead the development of scalable, testable, and high-performance applications.
• Provide leadership and mentorship to other ML engineers, fostering the growth of a strong Machine Learning Engineering organization.