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Tier-1 employer, mid-level ML role, metro location, and broad skillset amplify competition.
ML engineering skills transfer across industries but require specialized technical experience.
Explicit 5–10 years requirement and mandatory ML domain expertise create stringent shortlisting.
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Design, develop, and deploy advanced AI/ML models and scalable data pipelines to solve complex business problems.
Provide technical leadership in AI solution design across cross-functional teams and contribute to enterprise-scale analytics initiatives.
Mentor junior team members and establish best practices to ensure consistency, governance, and alignment with project objectives.
Bachelor's or Graduate Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field; or equivalent experience.
5–10 years of experience in machine learning, data science, or software engineering, preferably in large-scale or enterprise environments.
Proficiency in Python, SQL, distributed computing (e.g., PySpark), and cloud platforms (Azure, AWS, GCP).
Experience building scalable ML workflows, data pipelines, and end-to-end AI/ML solutions.
Experienced in designing and deploying complex machine learning models with measurable business impact in enterprise settings.
Capable of technical leadership and cross-functional collaboration to align AI solutions with business goals.
Skilled in developing reusable AI/ML frameworks and mentoring teams in best practices and scalable architectures.