Machine Learning Engineer II
Role details
Job location
Tech stack
Job description
- Engineered for Scale: You take pride in writing clean, maintainable, and high-performing code that operates seamlessly at massive consumer scale.
- Curious & Adaptable: You stay at the bleeding edge of AI/ML trends-eager to test, adopt, and deploy emerging technologies and models into real-world applications.
- Collaborative Partner: You thrive in cross-functional, global engineering environments, working closely with Tech Leads, Architects, and Engineers to deliver robust features.
- Pragmatic Problem Solver: You know how to balance engineering trade-offs-optimizing for speed, system performance, cost efficiency, and failure-recovery mechanisms in AI/ML solutions.
Responsibilities
- Drive Personalization at Scale: Design, build, and deploy high-throughput AI/ML and NLP models that uncover user insights and power personalized experiences across Yahoo Mail.
- Embed AI-Driven Workflows: Leverage advanced AI tools and modern AI-assisted engineering practices to optimize daily coding, testing, and iteration cycles.
- Process Massive Datasets: Apply machine learning algorithms and big data pipelines to extract value from trillions of data points while maintaining high security and performance standards.
- Build Resilient Systems: Implement robust feedback loops and fallback strategies to handle model edge cases gracefully and preserve seamless user experiences.
- Architectural Evolution: Participate in migrating backend ML services and data infrastructure to a public cloud architecture (GCP).
- Cross-Functional Collaboration: Collaborate across global engineering groups to integrate Mail Intelligence models into core product platforms seamlessly.
- Uphold Engineering Standards: Maintain exceptional code quality, conduct thorough code reviews, and advocate for sustainable architectural designs.
Requirements
- Education: Bachelor's degree in Computer Science, Data Science, or a related technical field; Or, equivalent experience.
- Experience: 2+ years of hands-on experience developing, training, and deploying machine learning models or data-intensive backend software systems.
- Core Languages: Strong proficiency in Python or Java (C++ is a plus).
- ML Stack & Models: Hands-on experience with modern frameworks like PyTorch, TensorFlow, Hugging Face, or Scikit-learn, with exposure to both discriminative and generative AI architectures.
- Model Deployment: Experience deploying models into production using runtimes/frameworks such as vLLM, TensorRT-LLM, Triton Inference Server, or ONNX Runtime.
- Modern AI Workflows: Familiarity with AI-assisted developer environments (e.g., Cursor, GitHub Copilot, Claude, ChatGPT) for day-to-day code generation and optimization.
- Data Processing: Experience working with distributed big data platforms (e.g., Spark, Hadoop, Kafka).
- Communication: Strong written and verbal communication skills with a track record of collaborating effectively with international teams., * Cloud Experience: Direct experience deploying AI/ML workloads on public cloud platforms, preferably Google Cloud Platform (GCP).
- Domain Knowledge: Prior experience building systems for high-volume email platforms, messaging networks, or large-scale consumer applications.
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.
Benefits & conditions
The compensation for this position ranges from $111,000.00 - $231,250.00/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.