Scientist Machine Learning (Cheminformatics)

TL;DR

Scientist Machine Learning (Cheminformatics): Developing and implementing machine learning models for ingredient discovery with an accent on computational chemistry, receptor biology, and multi-objective optimization. Focus on building scalable modeling tools, integrating AI with chemical data, and deploying workflows on cloud infrastructure to transform molecule discovery processes.

Location: Must be based in Princeton, NJ or Long Island City, NY

Salary: $100,000–$140,000

Company

hirify.global is a global science-based company focused on nutrition, health, and beauty, leveraging cutting-edge technology to drive sustainable industrial innovation.

What you will do

• Develop and implement machine learning models to support the ingredient discovery pipeline.
• Apply neural network architectures and multi-objective optimization to solve complex chemical design problems.
• Deploy and manage machine learning workflows on Azure and AWS cloud infrastructure.
• Collaborate with chemists, biologists, and perfumers to translate scientific requirements into user-friendly modeling tools.
• Utilize modern tools including generative AI, agentic workflows, and graph data models.
• Stay current with advancements in machine learning and cheminformatics to drive team innovation.

Requirements

• Ph.D. in Cheminformatics, Computational Chemistry, Computer Science, AI, or Quantitative Finance/Economics.
• 2-5 years of academic or industrial experience in cheminformatics or computational chemistry.
• Strong proficiency in Python and data science libraries (NumPy, SciPy, Pandas, Scikit-Learn, PyTorch, TensorFlow).
• Expertise in cheminformatics toolkits such as RDKit.
• Deep understanding of machine learning algorithms, graph neural networks, and multi-objective optimization.
• Must be authorized to work in the United States.

Culture & Benefits

• Opportunity to work on high-impact innovations in health, nutrition, and beauty.
• Access to in-house training courses and professional development.
• Comprehensive total rewards package including annual incentive pay and retirement savings.
• Health care coverage and paid time off.
• Multicultural and interdisciplinary team environment.