Machine Learning Software Engineer - HYBRID

In this role, you will design, build, and optimize robust ML models, data pipelines, and intelligent agentic solutions. You will be responsible for the full lifecycle of model deployment, transforming experimental code into production-ready software by applying rigid development best practices (TDD, CI/CD). Collaborating cross-functionally with data scientists, architects, and product teams, you will establish automated MLOps infrastructure—including monitoring, validation, and drift detection—to ensure system reliability in an AWS environment.

Advantages
Cutting-Edge AI Scope: Direct involvement in building and optimizing both traditional ML models and next-generation Agentic solutions with a high degree of autonomy.

End-to-End Technical Ownership: Lead the operational deployment (MLOps) of AI models, directly influencing infrastructure automation, model tracking, and system performance.

Cross-Functional Collaboration: Serve as the technical softw...