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Metro location plus broad AI/ML skill requirements increase applicant density, yielding medium competition.
Role requires deep AI/ML, MLOps, and LLM expertise, making cross-industry fit highly domain-sensitive.
Explicit 12+ years requirement plus extensive mandatory ML, MLOps, cloud, and LLM toolset demands high strictness.
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Lead AI/ML operational and platform engineering across the organization to ensure technical excellence in AI/ML technology landscape.
Provide architecture guidance, technical leadership, and mentor AI Engineering, Data Engineering, and Platform teams.
Drive adoption and enablement of AI/ML platforms, tooling, best practices, and optimization including cloud-native and containerized environments.
Minimum 12 years of professional experience, including at least 10 years in IT, software engineering, or data science and 5 years with AI/ML technologies in production.
At least 3 years in a technical leadership, architecture, or senior engineering role.
Experience designing and implementing large-scale AI/ML solutions and working with cloud platforms (Azure, AWS, GCP) and container orchestration (Kubernetes, Docker).
Must have technical skills in ML frameworks (TensorFlow, PyTorch, scikit-learn), AI/ML platforms (Azure AI, AWS SageMaker, Google Vertex AI), large language models, MLOps tools, data engineering, and monitoring/observability tools.
Experienced in translating business requirements into scalable AI/ML technical solutions and overseeing solution optimization and compliance.
Operates effectively in cloud-native and containerized environments with strong architecture and troubleshooting capabilities in AI/ML stacks.
Skilled at leading cross-functional teams including AI Engineering, Data Engineering, and Platform teams to drive technical excellence and continuous improvement.