
Specializing in home improvement.
Software Engineer – Full Stack_Java_React_ML at Lowe's
About the role
Innovate in Bengaluru
This position is based at our on-site office in Bengaluru. Lowe's 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 Lowe’s
Lowe’s is a FORTUNE® 100 home improvement company serving approximately 16 million customer transactions a week in the United States. With total fiscal year 2024 sales of more than $83 billion, Lowe’s operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Mooresville, N.C., Lowe’s 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 Lowes.com
Lowe’s India, the Global Capability Center of Lowe’s Companies Inc., is a hub for driving our technology, business, analytics, and shared services strategy. Based in Bengaluru with over 4,500 associates, it powers innovations across omnichannel retail, AI/ML, enterprise architecture, supply chain, and customer experience. From supporting and launching homegrown solutions to fostering innovation through its Catalyze platform, Lowe’s India plays a pivotal role in transforming home improvement retail while upholding strong commitment to social impact and sustainability. For more information, visit Lowes India
Job Summary:
The primary purpose of this role is to translate business requirements and functional specifications into scalable technical solutions, with a strong emphasis on machine learning–driven systems. You will design and deliver robust application code, integrate ML models into production environments, and contribute to building intelligent, data-driven enterprise applications.
This role involves close collaboration with stakeholders and cross-functional teams to communicate project progress, propose ML-based solutions, and ensure successful delivery of business outcomes.
Roles & Responsibilities:
- Translate business requirements into scalable technical solutions, with a focus on ML-driven features and systems.
- Collaborate with product and data teams to identify opportunities for ML-based solutions.
- Develop and maintain backend services using Java, Spring Boot, and Python, and build responsive UIs using ReactJS.
- Build and manage data pipelines, feature engineering workflows, and model evaluation processes.
- Deploy ML models using APIs and microservices architecture.
- Work with PostgreSQL and other data stores for structured and semi-structured data.
- Conduct root cause analysis and participate in code reviews for both ML and application code.
- Partner with product and business teams to identify opportunities for machine learning integration and data-driven decision-making.
- Develop and maintain full-stack applications using modern technologies (backend, frontend, and data layers).
- Test applications and ML components using TDD/BDD practices to ensure reliability and performance.
- Conduct root cause analysis for both application and model-related issues, including performance degradation.
- Participate in code reviews across both software and ML components to ensure quality and best practices.
- Implement and maintain CI/CD pipelines, including support for ML model deployment and monitoring (MLOps practices).
- Solve complex technical and ML-related challenges with a focus on scalability, maintainability, and efficiency.
Years of Experience:
- 3+ years of software development experience, including strong exposure to ML implementation.
Required Minimum Qualifications
- Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
- 3+ years of experience in software development or related roles.
- Hands-on experience in Machine Learning, including building and deploying models in real-world applications.
- 3+ years of experience working with SDLC and Agile methodologies.
- Proficiency in Python for ML development and at least one backend language (e.g., Java/Spring Boot).
- 3+ years of experience in some of Backend/microservices/API development, Frontend technologies (e.g., ReactJS), Database systems (e.g., PostgreSQL), DevOps/CI-CD tools and practices
Primary Skills (must have)
- Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
- 3+ years of software development experience, including strong exposure to ML implementation.
- Proven experience building and deploying machine learning models in production environments.
- Strong programming skills in Python (for ML) and Java/Spring Boot (for backend services).
- Experience with ML frameworks/libraries (e.g., scikit-learn, Tensor Flow, Py Torch).
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with Agile/Scrum and SDLC practices.
- Experience in some of: Backend/microservices/API development, Frontend (ReactJS or similar), Databases (PostgreSQL or similar), DevOps/CI-CD pipelines
- Core Focus:
Machine Learning, Model Deployment, Data Pipelines
- Languages/Frameworks:
Python, Java, Spring Boot, ReactJS
- ML Tools:
scikit-learn, Tensor Flow, Py Torch
- Database:
PostgreSQL
- Concepts:
Microservices, REST APIs, MLOps, CI/CD, TDD/BDD, Agile
- Nice to Have:
AI (NLP, CV, GenAI), Cloud, Docker/Kubernetes
Secondary Skills (desired)
- Exposure to broader AI concepts such as NLP, computer vision, or generative AI.
- Experience with MLOps practices (model versioning, monitoring, retraining pipelines).
- Familiarity with cloud platforms (AWS, Azure, or GCP) for ML deployment.
- Experience building end-to-end data-driven or intelligent systems in enterprise environments.
- 3+ years of experience in Machine Learning and Full Stack development in a production environment.
- Experience implementing end-to-end ML pipelines (data ingestion → model training → deployment → monitoring).
- Familiarity with MLOps tools and practices (model versioning, monitoring, retraining).
- Exposure to broader AI domains such as NLP, computer vision, or generative AI (nice to have).
- Experience developing and deploying enterprise-grade business systems.
- Familiarity with cloud platforms (AWS, Azure, or GCP) - ML Flow, Kube Flow for ML workloads.
Lowe’s is an equal opportunity employer and administers all personnel practices without regard to race, color, religious creed, sex, gender, age, 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 state or local law. Lowe’s wishes to maintain appropriate standards and integrity in meeting the requirements of the Information Technology Act’s privacy provisions.
Lowe's 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.
Required skills
Java
React
Full-stack development
REST APIs
Frontend development
Backend development
Problem solving
Collaboration
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About Lowe's

Lowe's
PublicSpecializing in home improvement.
10,001+
Employees
Mooresville
Headquarters
$11.2B
Valuation
Reviews
10 reviews
3.3
10 reviews
Work-life balance
2.8
Compensation
3.5
Culture
3.2
Career
2.5
Management
2.9
45%
Recommend to a friend
Pros
Friendly coworkers and team environment
Flexible scheduling and hours
Good benefits and health coverage
Cons
Poor management and lack of support
Limited advancement opportunities
High pressure and unrealistic expectations
Salary Ranges
54 data points
Lead/L5
Mid/L4
Senior/L5
Director
Lead/L5 · LEAD ANALYST, DACI ANALYTICS
1 reports
$149,023
total per year
Base
$130,021
Stock
-
Bonus
-
$149,023
$149,023
Interview experience
52 interviews
Difficulty
4.1
/ 5
Duration
21-35 weeks
Offer rate
23%
Experience
Positive 68%
Neutral 16%
Negative 16%
Interview process
1
Recruiter Screen
2
ML Coding
3
ML System Design
4
Research Discussion
5
Team Interviews
Common questions
ML fundamentals
Design an ML system
Research paper discussion
Statistical concepts
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