Software Engineer I,ITC

1 week ago

Bengaluru, Karnataka, India Nike Full time ₹ 10,00,000 - ₹ 20,00,000 per year

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 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

  • 1+ 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, 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

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