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Mid-level GenAI role, metro location, and broad skill requirements increase applicant competition.
Highly specialized GenAI and LLM skills reduce cross-industry transferability.
Explicit 3+ years plus many mandatory GenAI/ML stack requirements make shortlisting highly stringent.
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Build and deploy practical Generative AI applications including AI virtual assistants, AI agents, and content generation tools using core GenAI technologies and frameworks.
Manage end-to-end AI/ML solution delivery contributing to multi-client revenue and operational efficiency improvements.
Collaborate across product, design, business, and engineering teams to develop scalable, secure, and cost-effective AI systems on AWS and cloud platforms.
Minimum 3+ years in Data Science with at least 2+ years hands-on experience in building and deploying Generative AI applications.
Proficiency in Python and ML/AI libraries such as Hugging Face Transformers, PyTorch/TensorFlow, and experience with GenAI tools like AWS Bedrock, LangChain, vector databases, and LLM principles.
Experience in model training/fine-tuning (e.g., LoRA/QLoRA) and working knowledge of NLP concepts.
Work Experience Required: Minimum 3+ years in Data Science with relevant GenAI experience.
Demonstrated ability to deliver GenAI client solutions that drive measurable revenue and operational gains, indicating business and technical impact orientation.
Experience in diverse technical environments including cloud deployment (preferably AWS), cross-disciplinary collaboration, and fast-paced iterative development.
Portfolio of open-source contributions or personal GenAI projects and familiarity with full-stack development and MLOps practices for LLMs.