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Mid-level, popular AI role in a metro location with broad LLM skill requirements.
ML/AI skills are transferable across industries but require specialized model and LLM experience.
Explicit 3–5 years requirement plus mandatory LLM/ML stack and cloud experience increases filtering.
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Lead design, development, and deployment of scalable AI/ML solutions including LLMs, RAG pipelines, and Generative AI to support enterprise-wide AI adoption.
Provide technical direction and architectural oversight, ensuring AI solutions are performant, secure, compliant, and aligned with business objectives.
Collaborate across Product, Innovation, Technology, and Data Engineering to implement AI strategy and operationalize AI models and services in production.
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field required; Master’s preferred.
3–5+ years of hands-on experience developing and deploying ML/AI models in production with LLMs, NLP, and generative AI.
Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Hugging Face, scikit-learn; experience with cloud AI platforms like AWS SageMaker, Azure ML, or GCP Vertex AI.
Experience with RAG, prompt engineering, embeddings, vector databases, SQL skills, and familiarity with data engineering and MLOps practices.
Experienced in leading end-to-end AI solution delivery in enterprise environments, bridging technical and business domains.
Skilled in advanced AI techniques including LLMs, generative models, prompt engineering, and integration via APIs and microservices.
Able to translate business requirements into scalable AI architectures and maintain model governance and operational excellence.