Sr. AI/ML Infrastructure Engineer

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Requirements:

• 5+ years of industry experience building production-level ML platforms and infrastructure.
• Ability to write high-quality code in Python, Java, or Scala.
• Experience building production-ready RESTful APIs and scaling platforms for large user bases.
• Desire to own parts of an ML Platform with understanding of ML models and principles.
• Experience with containers and deploying applications to Kubernetes.
• Familiarity with LLMs and building infrastructure for LLM applications.
• Experience with relational and low-latency databases.
• Experience in transforming data in batch and streaming contexts.
• Ability to manage large projects from scoping to delivery.
• Strong communication and organizational skills, with the ability to simplify complex problems.

Responsibilities:

• Be part of a team building scalable infrastructure for training, evaluating, deploying, performing inference, and monitoring ML models.
• Build, deploy, and maintain generative AI services and applications.
• Create data systems to collect, clean, label, and store data used for model features.
• Deploy and manage applications in Kubernetes clusters.
• Collaborate with Machine Learning engineers to support experimentation platforms and training frameworks.
• Work with stakeholders to address requirements for ML infrastructure.