Machine Learning Scientist III (Agentic Merch)

Location: Boston, Massachusetts, United States

Annual base salary: USD 184,800–196,350

Company

hirify.global is an online retail platform building technology and science-backed solutions for home shopping, product discovery, merchandising, and assortment optimization.

What you will do

• Design, build, deploy, monitor, and iterate machine learning models for product relationships, demand identification, product grouping, and assortment optimization.
• Apply representation learning, similarity search, classification, and graph-based methods to structured and unstructured product data, including attributes, text, and images.
• Optimize model cost, efficiency, latency, and scalability using parameter-efficient fine-tuning, knowledge distillation, and hybrid machine learning approaches.
• Develop agentic AI workflows for schema definition, dataset generation, production relationship modeling, and LLM-based catalog validation.
• Define success metrics, conduct exploratory analysis on large retail datasets, and use findings to improve product curation and gap identification.
• Collaborate with product managers, engineers, supplier experience teams, and external AI research partners; mentor junior ML scientists.

Requirements

• Minimum 2+ years of experience with a PhD, 4+ years with an MS, or 6+ years with a BS in a quantitative STEM field.
• Strong Python and machine learning experience with PyTorch, XGBoost, or similar frameworks.
• Experience deploying and operating machine learning models in production at scale.
• Expertise in graph relationships, representation learning, embedding-based similarity search, multimodal data, and agentic workflows.
• Experience with large datasets and scalable data pipelines, balancing accuracy, latency, and operational cost.
• Strong written and verbal communication skills for collaboration with merchant, product, and engineering partners.

Nice to have

• Experience with large-scale ecommerce or catalog data.
• Familiarity with approximate nearest neighbors, graph-based ML, MLOps tooling, feature stores, MLflow, monitoring, Airflow, or Kubeflow.
• Experience with GCP, AWS, Azure, Docker, LLMs, or multimodal models.

Culture & Benefits

• Work with one of the largest and most complex retail catalogs, with measurable customer and supplier impact.
• Cross-functional collaboration with scientists, engineers, and product leaders.
• Hackathons and dedicated experimentation opportunities for new ML and AI approaches.
• Paid holidays, paid time off, medical, dental, vision, HSA/FSA, life insurance, and disability protection.
• 401(k) matching, tuition reimbursement, parental leave, family planning support, and mental health resources.
• Flexible work environment, employee discounts, fitness programs, and professional recognition.