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Mid-level ML/GenAI role in a metro with broad skillset requirements.
Role requires specialized ML/GenAI expertise, limiting cross-industry transferability.
Explicit 4–8 years requirement plus mandatory ML/GenAI, Python, AWS, and production experience.
Design, develop, and deploy scalable AI and machine learning solutions including traditional ML and generative AI applications.
Build production-grade AI services, APIs, and microservices with a focus on LLM-powered applications and AI copilots.
Monitor and improve model performance through validation, retraining, and applying explainability and auditability in business-critical AI applications.
4-8 years of experience in AI/ML or Data Science roles.
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering, or related field.
Strong Python programming skills and experience with AWS cloud services (including EKS, SNS, SQS).
Experience with machine learning algorithms, deep learning/NLP frameworks (TensorFlow or PyTorch), and building scalable REST APIs.
Experienced in developing end-to-end AI/ML applications with expertise in both traditional ML and generative AI within enterprise environments.
Comfortable designing scalable, cloud-native AI microservices applying software engineering best practices such as SOLID principles and clean coding.
Skilled in API development, prompt engineering, and integrating AI with event-driven architectures and vector databases for retrieval-augmented generation (RAG).