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Mid-level ML role in Bengaluru with common skillset and metro location yields high candidate density.
Core ML engineering skills (modeling, deployment) are highly transferable across industries.
Explicit 3-6 years plus mandatory production ML experience and specific tech proficiencies increases screening strictness.
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Build, train, and deploy end-to-end machine learning models independently for complex projects.
Design and maintain scalable ML pipelines, from data preprocessing to model serving in production.
Collaborate with cross-functional teams to translate business requirements into technical solutions and contribute to system architecture decisions.
Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or related field.
3-6 years of professional experience in machine learning engineering with production deployment experience.
Strong proficiency in Python, SQL, and experience with distributed computing frameworks such as Spark.
Work Experience Required: 3-6 years; notice period: Not explicitly mentioned in the JD.
Experienced with complex ML model development and deployment in production environments requiring autonomy.
Skilled in building robust ML pipelines, familiar with orchestration tools (e.g., Airflow) and ML platforms (e.g., MLflow).
Has practical expertise in modern AI frameworks, including applications with Large Language Models (LLMs) or Generative AI.