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Bengaluru location, early-career role, and generic engineer title increase applicant competition despite ML specialization.
Core ML engineering skills transfer across industries, although healthcare data sensitivity adds moderate domain bias.
Strict IIT/NIT and ≥8.0 CGPA requirement plus mandatory ML project experience enforces high filter.
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Develop and maintain production-grade Python and SQL services handling sensitive healthcare data with logging, monitoring, and reproducibility.
Build and own end-to-end machine learning, AI/GenAI pipelines or ML platform tooling including feature engineering, deployment, and evaluation.
Troubleshoot and improve live systems focusing on cost, latency, reliability, and implementing tests or monitoring to prevent recurrence.
Bachelor's degree in Computer Science, Information Technology, or related field from IITs, NITs, or premier institutes with minimum 8.0 CGPA.
0-1 years of relevant work experience.
Proficiency in Python, SQL, data structures, algorithms, and experience building ML/AI systems beyond notebooks.
Ability to operate across full development lifecycle including CI/CD, testing, and production deployment.
Experience or demonstrated skills in applied ML & evaluation, MLOps and cloud/deployment tooling, or LLMs, RAG, and agentic frameworks.
Comfort working with complex real-world data and sensitive healthcare or regulated domains is advantageous.
Capability to own production services end-to-end, balancing technical accuracy with operational reliability and cost.