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Mid-level ML role in Bangalore with broad requirements and generalist appeal increases applicant competition.
Core ML engineering skills transfer across industries, though domain-specific data knowledge may restrict some moves.
Explicit 3-6 years plus production ML and specific tooling requirements increases screening rigidity.
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Build, train, and deploy end-to-end machine learning models independently for complex projects.
Design and maintain ML pipelines spanning data processing to model serving.
Collaborate with cross-functional teams to translate business requirements into ML technical specifications.
Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or related field.
3-6 years of professional experience in machine learning engineering.
Proficiency in Python, SQL, and experience with distributed computing frameworks like Spark.
Experience building and deploying ML models in production environments.
Experienced ML engineer capable of working autonomously on well-defined, complex ML projects.
Strong data analytics skills including statistical analysis and business insight derivation.
Practical experience with AI frameworks and techniques, including LLMs or Generative AI applications, plus familiarity with tools like Airflow or MLflow.