Senior Staff Applied Scientist (ML)

Location: Seattle, USA

Salary: $159,000–$324,000 per year base pay

Company

hirify.global is a large global public e-commerce company building technology and services for shopping, food, logistics, and commerce operations.

What you will do

• Design and implement end-to-end machine learning systems for commerce risk detection, post-purchase experiences, logistics compliance, and related operations.
• Formulate business problems as machine learning problems and lead the ML vision and roadmap for large, complex projects.
• Build and optimize reproducible, scalable ML pipelines using Apache Spark, Airflow, Kubeflow, and MLflow.
• Define performance metrics, evaluate model impact, and identify opportunities for improvement.
• Collaborate with product, operations, and backend engineering teams to align technical solutions with business and customer goals.
• Mentor engineers and promote technical excellence, experimentation, and continuous learning.

Requirements

• Bachelor’s degree in computer science, electrical engineering, mathematics, statistics, or a closely related field.
• At least 8 years of professional experience in applied machine learning.
• Experience with machine learning, deep learning, statistical modeling, and production-grade ML systems.
• Proficiency in Python and/or Java.
• Role location: Seattle, USA.

Nice to have

• Master’s degree or PhD in a relevant technical field.
• Domain knowledge in fraud detection, customer support, or logistics.
• Experience leading cross-functional teams in a multicultural, global organization.
• Hands-on experience with TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, H2O.ai, Airflow, MLflow, Kubeflow, or Amazon SageMaker.

Culture & Benefits

• Startup culture with the resources of a large global public company.
• Annual bonus of 0–20% of base salary.
• Medical, dental, vision, life, AD&D, disability, FSA, and HSA benefits.
• 401(k) plan with company match.
• 18–21 days of paid time off, 12 paid holidays, and paid parental leave.
• Pre-tax commuter benefits and free electric car charging.

Hiring process

• Application review, phone interview, onsite or virtual onsite interview, and offer.
• The process may vary depending on the role and scheduling circumstances.