Software Engineer I,ITC

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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