about 3 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design and evolve production MLOps capabilities across the full ML lifecycle.
- Build systems for experiment tracking, artifact management, and production readiness.
- Develop reusable platform tooling and engineering standards.
- Build operational infrastructure for LLM and agentic systems.
- Design evaluation and monitoring frameworks for AI systems.
- Build and optimize large-scale training pipelines.
- Write clean, modular, production-grade Python services.
- Drive engineering quality through automated testing and CI/CD.
Requirements
- 5+ years of professional software engineering or MLOps experience.
- Significant experience building production ML infrastructure.
- Strong Python engineering skills with production-grade architecture.
- Understanding of the end-to-end ML lifecycle.
- Experience with large-scale data platforms like Databricks or Spark.
- Familiarity with MLOps frameworks such as MLflow or Kubeflow.
- Proven ability to design reusable workflow orchestration.
- Strong written and verbal communication skills in English.
Tech Stack
Categories
AI & MLData Engineering