Senior Machine Learning Scientist (Agentic AI)

Location: Boston, Massachusetts, United States

Annual base salary: $297,250–$298,625

Company

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

What you will do

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

Requirements

• 5+ years of experience with a PhD, 9+ years with an MS, or 10+ years with a BS in a quantitative STEM field.
• 2+ years of experience as a Tech Lead, preferably developing agentic AI workflows at scale.
• Strong Python and machine learning ecosystem experience, including PyTorch, XGBoost, or similar frameworks.
• Experience deploying and operating machine learning models in production and working with scalable data pipelines and complex datasets.
• Expertise in graph relationships, representation learning, embedding-based similarity search, graph-based machine learning, multimodal data, and agentic AI workflows.
• Must work from Boston, Massachusetts, United States.

Nice to have

• Experience with large-scale ecommerce or catalog data, including product attributes, taxonomy, text, and images.
• Experience with MLOps tools such as feature stores, MLflow, and monitoring systems.
• Experience with Airflow, Kubeflow, cloud platforms, Docker, LLMs, or multimodal models.

Culture & Benefits

• Work on a large and complex retail catalog with measurable impact on customers and suppliers.
• Collaborate in a cross-functional environment with scientists, engineers, and product leaders.
• Access hackathons and experimentation time for exploring new machine learning and AI approaches.
• Receive paid holidays, paid time off, health benefits, life insurance, disability protection, and caregiver support.
• Additional benefits include 401(k) matching, tuition reimbursement, parental leave, employee discounts, and professional recognition programs.