Min Experience: 12+ years Location: Mumbai, Maharashtra, India JobType: full-time
The incumbent shall be responsible for leading AI/ML operational and platform engineering functions across the organization. The focus of this role is to provide and ensure technical excellence in the AI/ML technology landscape and drive the adoption of AI solutions across business units.
Relevant Experience:
10 years’ experience in IT, software engineering, or data science related positions
5 years of direct experience with AI/ML technologies, platforms, and solutions in production environments.
3 years in technical leadership, architecture, or senior engineering role.
Experience in Designing and implementing large-scale AI/ML solutions and systems.
Experience working with cloud platforms and understanding of cloud-native architectures.
Experience with DevOps, CI/CD pipelines, and containerized deployments.
Responsibilities:
Deep dive technical investigation, analysis and troubleshooting across AI/ML technology stacks, frameworks, and infrastructure using appropriate diagnostic and monitoring tools.
Provide technical leadership and mentoring to AI Engineering, Data Engineering, and Platform teams, fostering a culture of technical excellence and continuous improvement.
Drive the enablement of AI/ML platforms, tooling, and best practices across the organization.
Provide architecture guidance and technical oversight for AI/ML solution design, implementation, and optimization.
Lead the evaluation, selection, and integration of AI/ML tools, frameworks, and cloud services (e.g., Azure AI, AWS SageMaker, Google Vertex AI).
Establish and maintain monitoring, logging, and observability standards for AI/ML systems and models.
Investigate opportunities for optimization of AI/ML technology stacks, including model performance tuning and infrastructure efficiency.
Work with solution architects and business stakeholders to translate business requirements into technical AI/ML solutions.
Provide support and enablement for containerized and cloud-native environments, specifically Kubernetes and serverless platforms.
Ensure compliance, security, and governance best practices are implemented across all AI/ML solutions.
Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
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