Ai Ml Engineer

Role summary

We are seeking a highly skilled AI Engineer to design, build, and deploy production-grade AI and Generative AI solutions that power core retail capabilities across merchandising, supply chain, pricing, stores, and digital commerce. This role is deeply hands-on and focused on turning AI models into reliable, scalable, and governed products using modern data and AI platforms

• Design and implement AI applications for retail scenarios such as product search, recommendations, personalization, content understanding, and customer/associate assistants (chat/voice).
• Translate highlevel product requirements into technical designs, model choices, and service interfaces that can be implemented and iterated quickly.
• Implement LLM and NLPbased solutions (e.g., retrieval augmented generation, document Q&A, summarization, classification) for internal knowledge assistants and customer facing experiences.
• Work with frontend and backend engineers to embed AI capabilities into web, app, store, and internal tools, focusing on usability and performance.

• Partner with data engineers to access and prepare data from POS, ecommerce, CRM/loyalty, product catalogs, and supply chain systems; design data contracts and schemas that support AI applications.
• Build and iterate on models using appropriate techniques (traditional ML, deep learning, embeddings, LLMs), balancing accuracy, robustness, and cost.
• Set up evaluation pipelines, offline metrics, and online experiments (A/B tests) to measure impact on key KPIs like conversion, engagement, attach rate, instock rate, and associate productivity.
• Instrument applications with logging, tracing, and dashboards to monitor quality, latency, and errors in production.

• Develop reliable, well tested APIs, microservices, and jobs that run in cloud environments (AWS/Azure/GCP), using modern Dev Ops/CI/CD practices.
• Own the full lifecycle of features you build from design and implementation through deployment, monitoring, and iteration.
• Contribute to shared libraries, templates, and best practices that make it easier for other teams to build AI features consistently.
• Collaborate across time zones, maintaining clear communication and documentation for stakeholders.

• Bachelors or Master’s degree in Computer Science, Engineering, Mathematics, or related technical field.
• 3–5 years of experience building and deploying AI/MLpowered applications in production, ideally in consumer, ecommerce, or retail environments.
• Strong programming skills in Python and experience with modern ML/AI frameworks (PyTorch, Tensor Flow, scikitlearn, Hugging Face, or similar).
• Experience with LLMs and NLP (prompt design, embeddings, vector databases, RAG) or strong willingness and demonstrable ability to ramp quickly.
• Hands-on experience with cloud platforms (AWS, GCP, or Azure), ML services (Sage Maker, Vertex AI, Azure ML) and Databricks.
• Experience building and consuming RESTful APIs, working with SQL/No
  
  SQL databases, and deploying services in cloud environments.
• Solid understanding of software engineering fundamentals: data structures, algorithms, testing, code reviews, and CI/CD.
• Strong communication skills and ability to collaborate with cross functional partners across time zones.

• Experience in retail, ecommerce, logistics, or similar high volume B2C contexts.
• Exposure to MLOps tools and concepts (feature stores, model registries, monitoring) and modern data stacks (Spark/Kafka/Airflow/dbt).