Software EngineerJavaReactJSData&ML

Innovate in Bengaluru

This position is based at our on-site office in Bengaluru. Lowes offers an ultramodern work environment complete with cutting-edge technology collaborative workspaces an on-site gym and clinic and other perks to enhance your work experience.

About Lowes

Lowes Companies Inc. (NYSE: LOW) is a FORTUNE 100 home improvement company serving approximately 16 million customer transactions a week with total fiscal year 2024 sales of more than $83 billion. Lowes employs approximately 300000 associates and operates over 1700 home improvement stores 530 branches and 130 distribution centers. Based in Mooresville N.C. Lowes supports the communities it serves through programs focused on creating safe affordable housing improving community spaces helping to develop the next generation of skilled trade experts and providing disaster relief to communities in need. For more information visit .

At Lowes India we are the enablers who help create an engaging customer experience for our $90 billion home improvement business at Lowes. Our 4000 associates work across technology analytics business operations finance & accounting product management and shared services. We leverage new technologies and find innovative methods to ensure that Lowes has a competitive edge in the market. To know more about Lowes India visit

About the Team

Lowes forecasting platform team is responsible for predicting future trends outcomes or events based on current and historical data. The primary goal is to generate AI/ML forecasts that help the business plan for future demand optimize resources reduce risk and make data-driven decisions.

Job Summary

• The primary purpose of this role is to design build and operate scalable software and machine learning solutions that enable Data & AI-driven products. The role combines strong software engineering fundamentals with ML/MLOps data engineering cloud-native development and AI-enabled engineering practices.
• The engineer will contribute across the full Software Development Lifecycle (SDLC) from solution design and development through testing deployment production support and continuous improvement. Key responsibilities include building robust data and feature pipelines productionizing and scaling ML models optimizing model training and inference and implementing model monitoring and lifecycle management.
• The ideal candidate will apply software engineering rigor to ML workloads leverage AI/ML platforms and automation to accelerate experimentation and deployment and partner with Data Science Data Engineering Product and Engineering teams to deliver reliable solutions that enable faster data-driven business decisions.

Roles & Responsibilities

Design develop test deploy and support scalable secure and maintainable software and ML solutions including backend services APIs cloud-native applications data integrations and ML-enabled services supporting Forecasting and AI products.

Translate business and functional requirements into technical designs and high-quality implementations contributing across the full Software Development Lifecycle (SDLC).

Build and maintain data ingestion transformation preprocessing feature engineering and post-processing pipelines to support ML model training experimentation and inference.

Partner with Data Scientists and Data Engineers to translate model requirements into production-ready engineering solutions and ensure high-quality reliable data is available for model development and execution.

Support the end-to-end ML lifecycle including experimentation model registration and versioning testing deployment orchestration inference and ongoing model management using enterprise AI/ML platforms.

Develop and maintain CI/CD and automation pipelines for software data pipelines and ML models to enable reliable and repeatable testing and deployments.

Implement monitoring and observability for applications data pipelines and ML models including system health data quality model performance and drift and operational metrics.

Optimize software ML workloads and data pipelines for performance scalability reliability and cost efficiency across cloud and enterprise platforms.

Apply engineering best practices including secure coding code reviews automated testing documentation performance optimization data governance security and compliance.

Support production systems through monitoring incident resolution root-cause analysis troubleshooting and continuous reliability improvements.

Collaborate with Product Data Science Data Engineering Architecture Security Infrastructure and business teams to deliver reliable Forecasting and AI capabilities that support business decision-making.

Participate in technical design discussions and code reviews contribute to engineering standards share knowledge with team members and evaluate modern technologies AI-enabled development tools and automation to continuously improve software quality and engineering productivity.

Years of Experience

2 - 5 years of experience in Software Data & ML engineering.

Education Qualification & Certifications

Bachelors/Masters Degree in Engineering Computer Science CIS or related field (or equivalent work experience in a related field)

Minimum 2 years of experience in applications powered by AI/ML with large dataset and Data Engineering.

1 year of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC)

Skill Set Required

Experience with Data engineering & building data/ML pipelines for AI/ML Models & business analytics & insights.

Java Springboot MicroservicesReactJS

Hand-on experience (real-time) & proficiency in building robust reliable & scalable data/ML pipelines for Analytics & AI/ML systems working with large sets of structured and unstructured data from disparate sources

MLOps tools and frameworks such as MLflow Kubeflow or Vertex AI

Foundational understanding of ML models

Strong understanding of cloud platforms (GCP AWS or Azure)

Experience managing model registry and implementing versioning best practices.

Model Serving Frameworks

SQL

Python

PySpark

Big Data systems - Hadoop Ecosystem (HDFS Hive MapReduce) or Cloud

Analytics database like Druid Data visualisation/exploration tools like Superset.

CICD

GIT

Secondary Skills (desired)

Apache Airflow Cloud Composer

GCP cloud experience Big Query

Trino/Presto

Experience working on Data Quality/Integrity theme Tools like Great Expectations.

Domain experience on retail forecasting or any other business forecast predictions/time series forecasting.

Lowes is an equal opportunity employer and administers all personnel practices without regard to race color religious creed sex gender age ancestry national origin mental or physical disability or medical condition sexual orientation gender identity or expression marital status military or veteran status genetic information or any other category protected under federal state or local law.