Software Engineer II, ITC

1 day ago


India Nike Full time

Job Description Who You'll Work With You'll be joining a dynamic, fast-paced Global FPE (Foundational Platforms Engineering) team within Nike. Our mission is to build and scale world-class cloud-native platforms, enabling Nike's data-driven decision-making and intelligent automation capabilities. This role sits right into AI-driven innovation helping to drive cutting-edge advancements in both analytics and intelligent automation. Collaboration and creativity are at our core, and we are passionate about leveraging cloud-scale data platforms and AI-powered automation to transform business operations. Who We Are Looking For We are seeking a Software Engineer II who brings deep expertise in Databricks, AWS Services, Cloud Platforms, and AI-driven automation. You are someone who thrives in building scalable, high-performance data platforms to improve efficiency, insights, and user experience. Key Skills & Traits - 2+ years of production experience in AI/ML model development, deployment, and maintenance - Proven expertise with Large Language Models (LLMs) and NLP tasks - Strong background in data science and cloud-based AI/ML services (Databricks preferred) - Expertise in MLOps/LLMOps for scalable model deployment and management - Advanced programming skills in Python, SQL, and automation frameworks - Worked in Cloud Platforms: Databricks(AI-ML) - MLOps/LLMOps and MLFlow - Passion for leveraging AI to enhance automation, efficiency, and analytics - Strong collaboration, problem-solving, and leadership skills, with the ability to drive initiatives across multiple teams. Good To Have - Data Processing: Pandas, NumPy, Spark. - DevOps: Docker, Kubernetes,DVC(Data Version control)/model monitoring and versioning. What You'll Work On As a Software Engineer II, you will play a crucial role in shaping, modernizing, and scaling by helping driving AI adoption and automation. Core AI/ML Engineer Responsibilities - Develop end-to-end ML pipelines with focus on production reliability. - Implement robust testing and validation frameworks for ML models. - Establish best practices for model versioning and reproducibility. - Build and optimize production-grade ML models . - Develop custom NLP solutions for text analysis and processing. - Create automated model evaluation and optimization pipelines. - Manage ML infrastructure on Databricks cloud platform. - Ensure scalability and cost optimization of ML deployments. - Maintain data quality and pipeline efficiency. - Maintain security and compliance implementations for ML systems. - Evangelize AI adoption, helping Nike teams unlock new automation opportunities.



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