Senior Software Engineer

Required Skills & Experience

• Python development experience
• Backend/API development experience, ideally with Java exposure as well
• GCP Cloud experience
• MLOps experience, including model training, validation, deployment, and serving
• Experience with Airflow / Cloud Composer or similar pipeline orchestration
• Model serving and optimization experience ○ NVIDIA Triton is what the team uses, but Triton itself is not required
• Experience building scalable APIs
• Comfortable understanding ML models and integrating them into production systems
• Hands-on experience using AI development tools such as Claude or Gemini to improve engineering productivity

Nice to Have Skills & Experience

• Search, retrieval, relevancy, or ranking experience
• Semantic search experience
• Ranking/retrieval model experience
• NVIDIA Triton
• Strong combination of Java + Python
• Prior exposure to ML-powered search platforms
• Ability to work across different backend technologies rather than being narrowly specialized

Job Description

Senior backend engineer supporting The Home Depot’s Search Relevancy, Retrieval, and Ranking team. This person will help productionize and integrate machine learning models developed by Data Science into the broader search platform. The role sits at the intersection of backend software engineering and MLOps. It is not a Data Scientist position and is not focused on building/tuning models from a pure Data Science perspective.

Day to Day:

• Integrate retrieval, ranking, semantic search, and other ML models into the search platform.
• Build and support Java and Python APIs that serve ML/search functionality.
• Work with Cloud Composer/Airflow pipelines supporting model training, validation, optimization, and deployment.
• Own aspects of model serving and performance optimization.
• Work closely with Data Science to understand models and successfully move them into production.
• Support multiple search models, including semantic retrieval and retrieval based on customer signals.
• Ramp into the broader search ecosystem over time rather than remaining narrowly focused on MLOps.
• Heavily leverage AI-assisted development tools as part of the engineering workflow.

This is a fully remote opportunity with a requirement of working CST or EST Hours. Limited travel may be required for planning and collaboration sessions. Compensation includes a target hourly rate of $52-$54/hr, with conversion salary negotiable.