ML Engineer II
MiQ (company site, opens in a new tab)2–4 yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Build scalable, production-ready AI solutions by bridging Data Science and Software Engineering skillsets, including reusable feature tables and ETL pipelines.
- Optimize model training, deployment, and inferencing for performance and reduce time to market.
- Develop and maintain monitoring systems for ML solutions to track performance, reliability, and institutionalize MLOps best practices.
Minimum Requirements
- 2 - 4 years of hands-on experience deploying and monitoring ML models in production (Databricks preferred).
- Strong proficiency in Python and experience with distributed data processing frameworks like PySpark.
- Experience building scalable ETL pipelines and end-to-end ML model training, inferencing, and retraining pipelines.
- Familiarity with version control, CI/CD, unit testing, and quality code standards.
Ideal Candidate Profile
- Operates effectively at the intersection of Data Science and Software Engineering to deliver scalable ML solutions.
- Experienced in cross-functional collaboration with Data Scientists, Engineers, and Product Managers to meet business goals.
- Focuses on operationalizing MLOps practices and improving ML ecosystem with attention to performance, reliability, and business impact.