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Respected global brand but senior, specialized ML role reduces applicant pool.
MLOps, Python, and cloud skills are highly transferable across industries.
Master's requirement plus mandatory production MLOps, Python, AWS and leadership makes screening stringent.
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Lead the design, analysis, implementation, and integration of AI model serving solutions focused on performance, reliability, scalability, and cost optimization.
Define and implement safe rollout and rollback strategies, establish resilience patterns, and ensure operational readiness for AI and Generative AI production services.
Provide technical leadership by mentoring engineers, conducting design and code reviews, and coordinating with cross-functional teams like Platform, MLOps, Reliability, Security, and Product.
Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field.
Strong experience delivering production-grade software systems, including expertise in Python development.
Experience with containerized, microservice-based architectures, API design/versioning, AWS, CI/CD pipelines, and DevOps practices.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in leading technical initiatives and mentoring engineers in AI engineering or software development contexts.
Strong background in designing and scaling AI-serving architectures with operational focus on performance and resilience.
Comfortable working collaboratively with multidisciplinary teams in complex, production-grade AI environments.