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Medium: known employer and metro location, but senior and niche LLM/MLOps skills limit applicant pool.
High: specialized ML, LLM and MLOps expertise required, reducing cross-industry transferability.
High: many mandatory technical skills, ML/LLM frameworks, deployment and MLOps requirements.
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Design, develop, and deploy end-to-end AI applications including data ingestion, model training, and production inference.
Build and optimize machine learning and generative AI solutions, including APIs for real-time and batch use cases.
Lead technical guidance, mentor team members, and align AI projects with enterprise and industry standards.
Strong expertise in machine learning frameworks TensorFlow and PyTorch.
Advanced proficiency in Python and SQL for data processing and solution development.
Experience with generative AI / LLM applications, data engineering, feature engineering, and AI system design including MLOps.
Work Experience Required: Not explicitly mentioned in the JD.
Broad hands-on experience deploying scalable AI solutions from data to production inference.
Proven ability to lead and mentor technical teams in machine learning projects.
Strong domain knowledge to translate business requirements into AI-driven solutions with strategic vision.