Senior Software Engineer - Machine Learning (Remote)

The Home Depot is seeking a highly skilled and highly motivated Senior Software Engineer to join the Discovery Intent and Guidance (DIG) team. This role involves designing, building, and modernizing systems that drive recommendation engines, integrating machine learning capabilities to enhance product discovery experiences.

Responsibilities:

• Develops, tests, deploys, and maintains software, with a clear understanding of the value the software is to provide; Takes on new opportunities and tough challenges with a sense of urgency, high energy and enthusiasm; Consistently achieves results, even under tough circumstances; Develops test suites (functional, destructive, etc) to enable success, rapid deployment of code to production; Takes a broad view when approaching issues; using a global lens
• Learns through successful and failed experiment when tackling new problems; Actively seeks ways to grow and be challenged using both formal and informal development channels
• Collaborates with other team members in agile processes; Creates new and better ways for the organization to be successful; Works the Product Team to ensure user stories are valuable, developer ready, easy to understand and testable; Delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences; Adapts approach and demeanor in real time to match the shifting demands of different situations; Relates openly and comfortably with diverse groups of people
• Helps grow junior engineers by providing guidance on modern software development frameworks, and leading technical discussions

Requirements:

• Must be eighteen years of age or older
• Must be legally permitted to work in the United States
• The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job
• 3 years of work experience
• None leadership experience
• 3-5 years of experience
• Languages — Strong in at least one of: Java, Scala, Python
• Microservices — REST APIs, gRPC, event-driven architecture (Pub/Sub, Cloud Tasks)
• System Design — Distributed systems, scalability, fault tolerance, API gateway patterns
• GCP Core — Compute Engine, GKE, Cloud Run, Cloud Functions, IAM
• BigQuery — Advanced SQL, partitioning, clustering, cost optimization
• Pipelines — Dataflow (Apache Beam), Dataproc (Spark), batch and streaming
• Storage — Bigtable, Cloud Storage, Firestore
• Orchestration — Cloud Composer (Airflow), Workflows
• Vertex AI — Model training, hyperparameter tuning, pipelines, model registry
• Frameworks — TensorFlow, PyTorch, scikit-learn
• MLOps — Model serving (Vertex AI Endpoints), monitoring, retraining pipelines
• Feature Store — Vertex AI Feature Store
• Search ML — Ranking, relevance tuning, embeddings (nice to have)
• AI & LLM Gemini — Gemini API, Gemini Pro, multimodal usage Vertex AI
• Generative AI — Model Garden, grounding, tuning
• RAG — Retrieval Augmented Generation, Vector Search (Vertex AI Vector Search)
• Agentic AI — Multi-agent frameworks, tool use, autonomous workflows