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Tier-1 brand and hybrid role increase attraction, but senior specialized ML requirement limits density.
Advanced ML engineering, distributed systems, and production infra needs make cross-industry transfers limited.
Explicit 12+ years, mandatory Kubernetes, CI/CD, production ML and language requirements make hiring filters strict.
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Architect and build event-driven, distributed systems for large-scale data procurement, annotation, and storage supporting the Intelligent Agreement Management platform.
Lead development of production-grade data pipelines enabling analytics, model evaluation, and machine learning model development at scale.
Serve as primary technical liaison for Applied Science and Product teams, translating business requirements into timely deliverables for ML-powered products.
12+ years experience with Bachelor’s degree, or 8+ years with Master’s degree, or equivalent experience in a related field.
Proven experience leading engineering projects from ideation through production independently and mentoring junior engineers.
Expertise in building and consuming production-grade RESTful and gRPC web services.
Professional experience with cloud deployment technologies including Kubernetes and Docker, and strong knowledge of CI/CD, integration testing, and test-driven development.
Experienced in architecting scalable, reliable, and high-performance AI-driven software systems and infrastructure.
Proficient in Java and Python with expert-level skills in writing and architecting applications across technology stacks.
Comfortable working independently with strong technical leadership, guiding distributed service architecture and collaborating cross-functionally with science and product teams.