Job Summary:
We are seeking an experienced AI Engineer to design, develop, and deploy advanced AI/ML solutions that enhance retail business capabilities, customer experiences, and operational efficiency. The ideal candidate will work closely with business stakeholders, data scientists, engineers, and product teams to build scalable AI applications leveraging machine learning, generative AI, and data-driven technologies.
Key Responsibilities:
- Design, develop, and deploy AI/ML models to solve complex retail business challenges, including customer personalization, demand forecasting, inventory optimization, pricing optimization, and recommendation systems.
- Develop and implement Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and AI agents.
- Build end-to-end machine learning pipelines from data preparation and model development to deployment and monitoring.
- Collaborate with data engineers, data scientists, product managers, and business teams to translate retail requirements into AI-driven solutions.
- Develop scalable AI applications using cloud platforms and modern AI frameworks.
- Optimize models for performance, accuracy, scalability, and production readiness.
- Implement MLOps practices including model versioning, CI/CD pipelines, monitoring, and automated deployment.
- Analyze large volumes of structured and unstructured retail data to identify trends, patterns, and actionable insights.
- Ensure AI solutions meet security, compliance, privacy, and responsible AI standards.
- Stay current with emerging AI technologies and recommend innovative solutions to improve retail operations.
Required Skills & Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- 5+ years of experience in AI/ML engineering, data science, or software engineering roles.
- Strong programming experience in Python and AI/ML libraries such as:
- TensorFlow.
- PyTorch.
- Scikit-learn.
- Pandas.
- NumPy.
- Experience developing and deploying machine learning models in production environments.
- Hands-on experience with Generative AI technologies:
- Large Language Models (LLMs).
- OpenAI models or similar AI platforms.
- Prompt engineering.
- RAG architecture.
- Vector databases (Pinecone, FAISS, Azure AI Search, etc.).
- Experience with NLP, recommendation engines, forecasting models, and predictive analytics.
- Strong understanding of data structures, algorithms, APIs, and cloud-based AI solutions.
