Role Overview
The Junior AI/ML Architect supports the design and implementation of scalable artificial intelligence and machine learning solutions tailored to retail business needs. The role focuses on translating retail use cases such as demand forecasting, personalization, pricing optimization, and supply chain analytics into robust AI-driven systems.
Collaboration with cross-functional teams ensures alignment between data science models, enterprise architecture, and business objectives.
Key Responsibilities
- Assist in designing AI/ML architectures for retail use cases such as recommendation engines, inventory optimization, and customer analytics
- Translate retail business requirements into technical AI/ML solutions
- Support operationalization of machine learning models through MLOps practices
- Contribute to deployment of models in cloud or hybrid environments (Azure, AWS, GCP)
- Define and support data pipelines, feature engineering workflows, and system integrations
- Participate in model lifecycle management including training, validation, deployment, and monitoring
- Ensure compliance with data governance, security, and Responsible AI standards
- Create and maintain architecture documentation and design artifacts
- Track emerging AI/ML trends relevant to retail innovation
Required Skills & Qualifications
- Strong understanding of machine learning techniques (classification, regression, clustering, deep learning)
- Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Proficiency in Python programming
- Knowledge of data engineering concepts (ETL, batch and streaming pipelines)
- Familiarity with cloud platforms (Azure, AWS, or GCP)
- Understanding of APIs, microservices, and containerization (Docker, Kubernetes)
- Exposure to MLOps tools and lifecycle management
- Basic knowledge of system architecture patterns and scalable design principles
- Familiarity with integration architectures and RESTful services
Preferred Skills
- Experience in retail domain use cases (pricing, promotion optimization, churn prediction, demand forecasting)
- Exposure to GenAI and LLM-based solutions for customer engagement or product discovery
- Familiarity with data platforms such as Databricks, Snowflake, or BigQuery
- Understanding of real-time analytics and event-driven systems
- Knowledge of Responsible AI and ethical AI frameworks
Soft Skills
- Strong analytical and problem-solving capabilities
- Effective communication and documentation skills
- Ability to work in cross-functional, agile teams
- Continuous learning mindset and adaptability
Key Deliverables
- AI/ML solution architecture designs and diagrams
- Deployed and monitored retail AI pipelines
- Technical documentation and implementation guidelines
- Scalable AI solutions aligned with retail business needs
Career Progression
- AI/ML Architect
- Retail AI Solutions Architect
- Lead AI Engineer / AI Platform Architect
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