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Senior, niche ML role in hybrid Bangalore-market at a mid-tier fintech yields moderate applicant competition.
Core ML engineering skills transfer broadly, though fintech domain knowledge moderately increases fit sensitivity.
Explicit 9–12 years requirement plus mandatory ML frameworks, programming, and cloud skills enforces strict filters.
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Own the design, building, and scaling of production-grade AI systems that deliver measurable business impact.
Manage end-to-end AI solutions lifecycle, including problem definition, deployment, adoption, and continuous improvement.
Collaborate across Product, Engineering, and Delivery teams to translate opportunities into scalable AI capabilities like agentic workflows and GenAI-powered systems.
Bachelor’s degree in a related field.
9–12 years of relevant experience in machine learning model development and deployment.
Proficiency in programming languages such as Python, R, or Java and ML frameworks like TensorFlow, PyTorch, scikit-learn.
Work Experience Required: 9–12 years relevant experience.
Experienced in leading AI system design and deployment with measurable business outcomes.
Strong background in statistics, optimization, probability theory, and experimental methodologies applied to ML solutions.
Comfortable working within cross-functional teams and mentoring junior engineers in a hybrid work environment.