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 Key responsibilities AI System Design and Engineering 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., retrievalaugmented generation, document Q&A, summarization, classification) for internal knowledge assistants and customerfacing experiences. Work with frontend and backend engineers to embed AI capabilities into web, app, store, and internal tools, focusing on usability and performance. Data, modeling, and evaluation Partner with data engineers to access and prepare data from POS, ecommerce, CRM/loyalty, product catalogs, and supplychain 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. Engineering excellence Develop reliable, welltested APIs, microservices, and jobs that run in cloud environments (AWS/Azure/GCP), using modern DevOps/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. Minimum qualifications 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, TensorFlow, 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 (SageMaker, Vertex AI, Azure ML) and Databricks. Experience building and consuming RESTful APIs, working with SQL/NoSQL 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 crossfunctional partners across time zones. Nice to have Experience in retail, ecommerce, logistics, or similar highvolume B2C contexts. Exposure to MLOps tools and concepts (feature stores, model registries, monitoring) and modern data stacks (Spark/Kafka/Airflow/dbt). #J-18808-Ljbffr