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Tier-1 brand but senior, specialized principal ML role reduces mid-level applicant density.
Requires deep ML platform, MLOps, and cloud expertise, limiting cross-industry transferability.
Explicit 12+ years, principal-level ML experience and specific cloud/MLOps toolsets required.
Lead architectural vision, technical design, and implementation of large-scale data and AI platforms ensuring robustness, security, and high performance.
Set technical standards and best practices for software development, agentic AI systems, and ML cloud infrastructure across multiple teams.
Collaborate with global stakeholders to align technology roadmaps with business priorities and oversee end-to-end project lifecycles including security and compliance.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, IT, Machine Learning, AI systems, or related field; Master’s in AI/ML/Generative AI highly desired.
12+ years in software engineering with at least 5 years in senior leadership or principal engineer role.
Expertise with AI cloud-native architectures (AWS SageMaker, DataBricks, Azure ML, GCP/Vertex AI) and modern ML stacks (LLMs, PyTorch, TensorFlow, Spark).
Proficiency in Python, Java, Scala or Go; experience with DevOps, automation, CI/CD pipelines, infrastructure as code, and security/compliance in enterprise environments.
Senior technology leader with proven ability to drive large-scale AI platform architecture and engineering standards in fast-paced, agile environments.
Experienced in mentoring senior engineers and influencing cross-functional global teams to deliver strategic technology solutions.
Strong expertise in integrating emerging AI/ML technologies and managing complex projects with focus on robust, secure, and scalable systems.