Machine Learning Scientist III (Ads, Search & Recommendations)

Location: Hybrid in Seattle, Washington, United States; in-office Tuesday–Thursday and remote Monday and Friday

Annual base salary: $194,040–$206,167

Company

hirify.global is an online retail platform that uses technology and machine learning to help customers discover home products.

What you will do

• Build and optimize candidate-generation and retrieval pipelines for personalized product recommendations and advertising.
• Apply deep learning, representation learning, sequence modeling, embeddings, and multi-modal modeling to user, product, and contextual signals.
• Develop scoring, ranking, and ad-allocation systems that balance personalization, relevance, and business impact.
• Address recommendation challenges including cold start, data sparsity, product compatibility, and seasonality.
• Collaborate with product managers, engineers, data scientists, and business partners on end-to-end ML projects.
• Contribute to internal knowledge sharing, technical documentation, and external ML conferences.

Requirements

• 2+ years of experience with a PhD, 4+ years with an MS, or 6+ years with a BS in a quantitative STEM field.
• At least 1 year of industry experience as an ML engineer, applied scientist, or research scientist delivering recommendation, search, or ranking projects autonomously.
• Expertise in recommendation systems, candidate generation, ranking algorithms, and user-item modeling.
• Strong understanding of sequence modeling, GCNNs, and/or embedding-based personalization.
• Strong Python proficiency and experience deploying machine learning models in production.
• Experience with GCP services including BigQuery, GCS, Vertex AI, and Composer, plus Airflow, MLflow, and Docker.

Culture & Benefits

• Hybrid work environment with a flexible schedule.
• Paid holidays, paid time off, medical, dental, vision, HSA/FSA, life insurance, and disability protection.
• 401(k) matching, tuition reimbursement, and tax-advantaged accounts.
• Parental leave, family planning support, caregiver services, and global adoption and surrogacy policies.
• Mental health support, fitness discounts, employee discounts, volunteer leave, and professional recognition programs.