AI/ML & Generative AI Developer

Job Description – AI/ML & Generative AI Developer Location (Preferred): Onsite – Pleasanton, CA / Plano, TX Client Overview Our client is seeking an experienced AI/ML & Generative AI Developer with strong data science and engineering expertise. The ideal candidate will have a background in retail or departmental store environments and experience working on forecasting models, explain ability layers, and cost/allowance/markdown-related use cases in the grocery domain. Role Overview As an AI/ML & Generative AI Developer, you will be responsible for building and implementing advanced machine learning and generative AI solutions to address critical business problems. You will design, develop, and deploy predictive models, integrate AI into cloud-native applications on Azure, and collaborate with cross-functional teams to deliver enterprise-grade solutions. This role requires strong programming skills, practical experience with ML/GenAI frameworks, and a passion for innovation. Key Responsibilities Model Development • Develop predictive models using supervised, unsupervised, and semi-supervised learning techniques. • Build forecasting models with explain ability layers tailored to retail and grocery business needs. • Apply algorithms such as regression, classification, clustering, and ensemble methods. Data Analysis & Feature Engineering • Perform exploratory data analysis (EDA), preprocessing, statistical testing, and feature engineering. • Work with retail and grocery-specific datasets (cost, allowance, markdowns, sales, and promotions). Model Evaluation & Optimization • Evaluate models using metrics such as ROC-AUC, RMSE, and F1-score. • Conduct hyperparameter tuning and cross-validation. Model Deployment • Deploy models as APIs/services using Azure Kubernetes Service (AKS), Azure Functions, or App Services. • Integrate models into CI/CD pipelines and monitor their performance in production. Generative AI Development • Build GenAI applications using LLMs (GPT, LLaMA, Claude) for summarization, content generation, and conversational AI. • Implement embeddings for semantic search, similarity matching, and feature representation. • Leverage platforms such as Hugging Face, LLaMA, and vector databases (FAISS, Pinecone, Azure AI Search). Prompt Engineering • Design and optimize prompts using few-shot learning, prompt chaining, and Retrieval-Augmented Generation (RAG). Team Collaboration • Collaborate with data engineers, analysts, and business stakeholders to align solutions with organizational goals. • Work in agile environments using JIRA, participating in sprint planning, stand-ups, and retrospectives. Required Technical Skills • Strong proficiency in Python and ML/GenAI libraries (scikit-learn, TensorFlow, PyTorch, Transformers, Lang Chain). • Hands-on experience with Azure ML and Azure Open AI. • Solid understanding of LLMs, their architecture, and components. • Expertise in statistical techniques: descriptive statistics, probability distributions, hypothesis testing, correlation analysis, ANOVA, linear/logistic regression. • Experience with embeddings, semantic search, and feature representation. • Familiarity with vector databases (FAISS, Pinecone, Azure AI Search). Preferred/Good-to-Have Skills • Experience in the grocery or retail domain, especially with cost, allowances, and markdowns. • Prior background in forecasting models and model explain ability frameworks. • Knowledge of MLOps best practices, containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, ARM templates). • Experience in large-scale cloud-native application development on Azure.