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Metro location, popular ML role, and recognized company moderately increase applicant competition.
AI/ML and MLOps skills are broadly transferable, though enterprise RAG experience narrows fit.
Requires explicit 8+ years plus extensive mandatory ML, MLOps, cloud, and LLM skills.
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Design, develop, deploy, and maintain AI/ML-powered applications and intelligent systems across the full ML lifecycle including data preparation, model development, deployment, monitoring, and optimization.
Build scalable APIs and backend services integrating AI capabilities, leveraging LLMs, foundation models, and RAG techniques to solve complex business problems.
Lead and mentor engineering teams, contribute to architecture and technical decisions, and ensure software engineering best practices including CI/CD and secure coding are followed.
Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or related field.
Minimum 8 years of software engineering experience with significant hands-on AI/ML development.
Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience with cloud platforms (Azure, AWS, or GCP), containerization (Docker, Kubernetes), and building REST APIs/microservices.
Experienced in building and productionizing enterprise AI/ML solutions using foundation models, LLMs, and Generative AI frameworks like LangChain or LlamaIndex.
Strategic contributor with skills in MLOps pipelines, model optimization, monitoring, and automation for scalable AI applications.
Capable of leading technical initiatives, mentoring engineers, collaborating cross-functionally, and implementing software engineering best practices for secure, reliable AI products.