ML Model Integration Platform Engineer

What you'll do

• Develop and maintain runtime services, APIs, and automation for model deployment, versioning, and monitoring.
• Design and deliver platform components to integrate Large Language Models into the application stack.
• Build internal tools including CLIs, micro-services, and automation pipelines to improve developer experience.
• Drive architectural decisions for distributed systems to optimize reliability, throughput, observability, and cost efficiency.
• Architect and deliver systems that enable the safe deployment of ML-powered features.
• Map system-level changes to ensure platform resilience and future-proof technical approaches.

What we're looking for

• 5+ years of software engineering experience in building and operating production systems.
• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• Strong background in distributed systems with the ability to reason about scale, concurrency, and failure modes.
• Proven experience designing and implementing internal tools, automation, and service-level components.
• Proficiency in scripting and programming languages such as C/C++, Python, SQL, and Shell.
• Ability to collaborate cross-functionally and influence decisions through technical depth and clarity.
• Understanding and practical experience with containerization technologies (Docker) and orchestration platforms (Kubernetes) (preferred).
• Solid background in one or more major cloud providers (AWS, GCP, Azure) relevant to ML workloads (preferred).