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
- 2-5 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.
- Hand on experience in Machine Learning: Supervised and unsupervised learning, model building, evaluation, and optimizations.
- Hand on experience in Deep Learning: Neural networks, CNNs, RNNs, LSTMs, transformers, and LLMs ; LLM fine-tuning and deployment
- Completed projects in Natural Language Processing (NLP): Text pre-processing, tokenization, embeddings, sentiment analysis, named entity recognition (NER), anomaly detection
- Frameworks and Libraries: PyTorch, Keras, Scikit-learn, Hugging Face Transformers.
- Worked in Cloud Platforms: Databricks(AI-ML) - preferred / AWS (SageMaker)
- MLOps/LLMOps
- 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 opportunities.
