Senior AI/ML Engineer – R01572485
- Category
- AI & Data Engineering
- Skills
- See official employer job description
- Experience
- Senior
- Openings
- 4
- Apply by
- November 2, 2026
Job requirements
- Lead the design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness
- Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to support robust deployment and monitoring
- Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
- Drive platform-level technical decision-making and define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
- Collaborate with business, data, technology, and platform teams to translate AI architecture principles into production-ready capabilities
- Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms, supporting long-term scalability and business outcomes
- Maintain and improve AI model governance, version control, and documentation for ongoing operational excellence
- Expertise in enterprise-scale AI platform design and operationalization
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Advanced programming skills in Python and PySpark
- Experience with cloud-based AI platforms and modern data/AI architectures
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Hands-on experience with KubeFlow and BentoML for ML pipeline orchestration
- Competence in classification algorithms such as decision trees and SVM
- Experience with Great Expectations and Evidently AI for model validation
- Strong proficiency in regression analysis (linear and logistic)
- Statistical analysis and computing for large datasets
- Experience with GenAI architectures, large language models, and AI agents
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
- Understanding of AI observability and Responsible AI frameworks
- Experience developing reusable AI architecture patterns and accelerators
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate)
- Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate)
Responsibilities
• Lead end-to-end execution of projects and cross-functional deliverables for Senior AI/ML Engineer - R01572485.
• Collaborate closely with departmental peers and stakeholders to ensure seamless operational continuity.
• Monitor core performance KPIs, troubleshoot bottlenecks, and implement optimization protocols.
• Champion high quality standards, peer reviews, and comprehensive team documentation.
Candidate Skill Fit Analysis
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Estimated In-Hand Salary
New Tax Regime (AY 2026–27)Indicative estimate using standard assumptions for EPF, professional tax and Section 87A. Actual payroll, benefits and deductions vary by employer and individual.
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