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High due to Tier-1 brand, metro location, mid-level role, and broad AI skill requirements.
Low because ML/AI engineering and LLM production skills are broadly transferable across industries.
High because of explicit 6+ years, mandatory production ML/LLM experience, and specific toolset expectations.
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Design, build, deploy, and maintain scalable AI/ML applications supporting automation and business workflows.
Provide hands-on technical leadership including architecture decisions, model evaluation, code quality, and engineering practices.
Ensure AI systems are secure, reliable, maintainable, and meet enterprise standards across infrastructure, deployment, and support.
4-year degree in Science, Technology, Engineering, or Mathematics or equivalent experience; MS preferred in CS, AI, ML, Applied Math or related field.
6+ years of software engineering experience including building and operating production systems.
Strong proficiency in Python and experience with AI/ML frameworks like PyTorch, TensorFlow, LangChain, LlamaIndex, or Semantic Kernel.
Experience with AI/ML application deployment considerations including system design, architecture tradeoffs, CI/CD, monitoring, and operational support.
Experienced in end-to-end AI engineering including LLM-powered applications, agentic systems, and data-intensive AI solutions.
Comfortable translating ambiguous business problems into practical, scalable technical solutions working with cross-functional teams.
Able to lead, mentor, and elevate engineering quality while staying current with AI trends and engineering best practices.