Senior Machine Learning Engineer

Yahoo is a leading technology company known for its innovative consumer products, including Yahoo Mail. They are seeking a Senior Machine Learning Engineer to design and deploy AI/ML capabilities that enhance user experiences and insights across their platform.

Responsibilities:

• Architect & Personalize: Design, build, and deploy high-throughput AI/ML capabilities that power real-time personalization and deep insights for hundreds of millions of users
• GenAI & Agentic Systems: Spearhead the implementation and orchestration of production LLM-backed applications and agentic workflows (prompt engineering, tool integration, and automated feedback loops)
• AI-Driven Execution: Embed AI-first practices into daily development cycles using AI-assisted tools to accelerate iteration, improve code quality, and modernize engineering workflows
• Data-Driven Intelligence: Process petabyte-scale data streams using big data processing and ML techniques to derive key insights from mail metadata and content
• Inference at Scale: Deploy and optimize ML/LLM models for real-time production serving using modern frameworks (e.g., vLLM, TensorRT-LLM, Triton, ONNX Runtime)
• Resilience & Fallback Design: Implement automated feedback loops and graceful recovery paths to handle model failure modes smoothly, maintaining high service availability and user satisfaction
• Tradeoff Management: Balance compute costs, latency, quality, and model performance to optimize systems for massive consumer scale

Requirements:

• Bachelor's degree in Computer Science, Data Science, AI, or a related field; or, equivalent experience
• 5+ years of professional experience engineering and deploying production machine learning or data science systems at scale
• Proficient in Python or Java, with deep hands-on expertise in standard ML frameworks (PyTorch, TensorFlow, Hugging Face, Scikit-learn)
• Demonstrated experience building LLM-based applications or agentic systems (multi-step reasoning, tool usage, RAG, or autonomous workflows)
• Experience deploying and serving models in production using tools like vLLM, TensorRT-LLM, Triton Inference Server, or ONNX Runtime
• Hands-on experience processing large datasets using Spark, Hadoop, or cloud-native data pipelines
• Excellent verbal and written communication skills for effective collaboration with cross-functional and global engineering teams
• Direct experience building and scaling ML pipelines on Google Cloud Platform (GCP) or similar native public cloud environments
• Prior experience working with email systems, large-scale consumer web platforms, NLP, or search architecture
• Early adoption and proactive integration of modern developer tooling (Cursor, Claude, Codex) directly into daily development practices