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Tier-1 brand, metro location, and generalist lead engineer title increase competition density.
Strong ML/AI, Java microservices, and MLOps requirements make background fit highly domain-specific.
Explicit 8–10 years and mandatory Python, Java, ML, and MLOps skills imply high shortlisting strictness.
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Lead and influence the design and delivery of large-scale, complex technology and AI/ML solutions with enterprise-wide impact.
Develop standards, best practices, and scalable ML pipelines for machine learning applications, including deployment and MLOps.
Provide technical leadership through code reviews, mentorship, cross-team collaboration, and resolving complex technical challenges.
5+ years of software engineering experience (or equivalent experience/training/education).
8-10 years experience preferred in software engineering, machine learning, or AI solution development.
Mandatory skills: strong proficiency in Python (ML and data processing) and Java (application development, APIs, microservices).
Experience with ML frameworks (Scikit-learn, TensorFlow or PyTorch), NLP/Generative AI, MLOps, and building scalable APIs using Java Spring Boot and REST.
Experienced in leading enterprise-grade AI/ML projects involving model lifecycle automation and scalable deployment.
Skilled at integrating ML models securely and reliably into business-critical systems with a strong focus on performance and operational stability.
Capable of driving technological modernization and best practices, with demonstrated mentorship and leadership in complex engineering teams.