Lead AI Engineer

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

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

About the Team

DACI AI platform team engages in building and managing AI solutions and tools. AI Platform manages products and tools to enable teams across Lowe's to build AI solutions in terms of providing access to LLMs and tools required in building ML lifecycle on both on premise and cloud(GCP VertexAI).

Roles & Responsibilities:

Core Responsibilities:

• Leads the development of the AI platform and ensures the scalability of the platform accommodates a wide spectrum of ML models and integration of new AI advancements as APIs.
• Leads the architectural design, development, and implementation of sophisticated tools and frameworks that elevate ML experimentation and deployment, ensuring that the platform delivers high-end AI functionalities.
• Architects and orchestrates the management of graphics processing unit and central processing unit resources to enhance the performance of AI models while maximizing cost efficiency and resource utilization.
• Mentors and guides junior team members to ensure a seamless integration of AI models into the platform.
• Leads the creation and management of robust data movement strategies and pipelines, optimizing data flows to meet the requirements of intensive AI model training and inference processes.
• Leads initiatives for continuous improvement by evaluating platform performance analytics and gathering user feedback.
• Leads cross-functional teams, fostering a collaborative environment that merges deep technical knowledge with strategic business insights and a keen understanding of user needs.
• Champions the development and enforcement of rigorous security protocols and governance measures for the AI platform, ensuring data integrity and adherence to industry standards and best practices.

Years of Experience:

8 plus

Required Qualifications:

• Bachelor's degree in science, technology, engineering, math, or related field (or equivalent work experience in lieu of degree) and 6 years of experience executing and deploying data science, ML, and DL (fewer years may be accepted with a Master's or Doctorate degree), ML platform engineering, MLOps tools, and ML frameworks
• 6 years of programming experience in Java and/or Python
• 4 years of experience working with cross-functional partners

Preferred Qualifications:

• Master's degree in science, technology, engineering, math, statistics, physics, economics, data science, information science, or quantitative analytics
• 5 years of experience in SQL and NoSQL databases, Hadoop ecosystem, Druid, Trino, Big Query, Google Vertex AI

Skill Set Required

• Python Primary language for AI/ML model development, especially for deep learning frameworks.
• Strong knowledge of multiprocessing and multithreading in Python or C++ (Optional) for handling high-throughput systems.
• Docker, Kubernetes (for handling large-scale deployments).
• Knowledge of microservices architectures, message brokers like Kafka or RabbitMQ.
• Experience with serving models using TensorFlow Serving, Torch Serve, or Fast API. - Model deployment
• MLflow, Kubeflow, or DVC for managing the lifecycle of models. - model management
• Git, Jenkins, CI for continuous integration and deployment.

Deep Learning Frameworks and Image processing:

• Pytorch, tensorflow, - Building and deploying computer vision models.
• OpenCV, scikit-image, or PIL for basic image processing. should aware of these framework and hands on experience
• Nvidia deep learning stacks and model serving frame works - good to have
• Should have work experience with real-time or offline video processing pipeline with Deep learning application development
• Optimization & Performance Tuning – Ability to improve AI model performance and reduce latency.

Models Awareness:

• Computer Vision – Knowledge of CNNs, object detection, and image/video processing techniques.

• Must aware of object detection, classification and segmentation models ( Yolo, any open source model)

• Optimizing models for edge deployment using TensorRT, OpenVINO, or ONNX.
• Knowledge of tracking (SORT, DeepSORT) and semantic segmentation techniques. Awareness is enough

Secondary Skills (desired)

Good to have

• Techniques for reducing inference time, including model pruning, quantization, and optimized inference with TensorRT or ONNX Runtime.
• Prometheus, Grafana, and ELK Stack for monitoring and logging AI/ML models in production.
• Experience with large-scale data management tools such as Hadoop, Spark, and distributed databases
• Other programming languages JS, UI backend services related knowledge.

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.