Design and build ML platform and AI agents to speed model delivery
Architect cloud-native microservices on Kubernetes with IaC automation
Own end-to-end ML lifecycle: training, testing, deployment, monitoring
Evaluate tools based on workloads and performance
Collaborate with engineering, data science, and product teams to align ML with goals
Identify and fix reliability, scalability, and performance gaps early

🎯 Requirements

6+ years of software engineering delivering high-scale, production systems
Strong proficiency in Python
Experience with relational and NoSQL databases; AWS, Azure, or GCP
Experience with training, testing, deploying, and monitoring real-time ML models
Fluent with AI tooling like Cursor and Claude Code; interested in GenAI/LLMs
Familiarity with RAG, embeddings, mixture-of-experts, prompt crafting
Bachelor’s or Master’s in CS/Engineering/Statistics or related field
Ready to work in an office environment most days

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