Machine Learning Engineer

• AI-First Mindset: AI is core to how you work, innovate, and deliver results. You actively experiment with advanced tools (e.g., Claude, Cursor, Codex), integrate them into your daily development workflows, and measure success by how effectively you leverage AI to solve complex problems.
• Agentic Thinker: You have hands-on experience designing, orchestrating, and evaluating agentic systems (multi-step reasoning, tool integration, memory, autonomous workflows, and LLM-based agents) in production environments.
• Engineering Standards: You take extreme ownership of your work, bringing high engineering rigor, clean code practices, and a focus on building scalable, fault-tolerant architectures.
• Collaborative Partner: You thrive in cross-functional, global engineering environments, working closely with Tech Leads, Architects, and Engineers to deliver robust features.
• Continuous Learner: You stay on the cutting edge of rapid advancements in machine learning, generative models, and infrastructure trends, continuously bringing novel approaches into practice.

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.

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

The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity.

The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more.

Yahoo Mail is the ultimate Consumer Inbox with over 220 million monthly active users. We empower users to run the business of their lives through a fast, intuitive platform while managing billions of daily inbound connections and petabytes of efficient storage. Our engineering team is actively transitioning to a 100% native public cloud architecture. The Mail Intelligence Org develops intelligent capabilities at scale to uncover user interests, reveal habits, and personalize user journeys across Yahoo Mail and the broader Yahoo ecosystem. We manage billions of messages using advanced backend systems and state-of-the-art AI - including NLP, Generative AI, and autonomous agentic workflows. We are a team of passionate engineers dedicated to high coding standards, world-class architecture, and an owner's mindset.