Description

2+ Years of Advanced Analytics & AI Experience:** Proven track record of translating complex, ambiguous business problems into enterprise AI/ML solutions, backed by a strong quantitative background in Computer Science, Mathematics, or AI.
* End-to-End Generative AI & ML Lifecycle:** Proficient in architecting, fine-tuning, and deploying production-grade ML models and GenAI frameworks (LLMs, RAG, Transformer architectures) using Python and frameworks like PyTorch, TensorFlow, LangChain, or LlamaIndex.
* Productionization & LLMOps / MLOps:** Hands-on expertise moving models from prototype to enterprise-scale production, managing CI/CD for AI, automated retraining, vector database management, and low-latency serving architectures (batch/real-time API inference).
* AI Model Evaluation & Benchmarking:** Skilled in designing statistically rigorous evaluation frameworks (e.g., A/B testing, causal inference, hallucination detection, guardrails, and benchmark metrics) to measure model safety, accuracy, and business impact.
* Big Data & Distributed AI Pipelines:** Highly skilled in writing high-performance SQL/PySpark and leveraging distributed computing frameworks to prepare, vectorize, and process terabyte-scale datasets for model training and retrieval.
* Strategic Business Impact & Executive Storytelling:** Exceptional ability to translate complex AI capabilities, technical trade-offs, and cost/latency constraints into clear, actionable business strategies for product teams and executive leadership.
* Technical Leadership & Architecture Review:** Serves as a technical anchor by establishing AI engineering standards, conducting code and system design reviews, enforcing data validation/ethics, and mentoring junior AI developers

Key Skills

Education

Bachelor's degree