AI Chemist

Shanghai IBP, China · On-site

About this role

Job Summary

Looking for a role that challenges you while making an impact on products people use every day?

About the Role

We are seeking a highly motivated AI Chemist to support the discovery of next-generation fragrance ingredients molecules through the application of AI, computational chemistry, and data-driven design approaches. Working closely with the AI Chemist Leader, you will contribute to the design, screening, and optimization of novel molecular candidates by integrating computational tools, predictive models, and chemical knowledge.

.

Where You Will Make a Difference

In this role, you will contribute to the development and application of AI-driven discovery workflows that support the identification of novel fragrance molecules. You will help transform data into actionable molecular insights, support virtual screening campaigns, and collaborate with multidisciplinary teams to advance promising candidates into experimental validation.

Through your work, you will help strengthen IFF's AI-powered discovery capabilities and contribute to building a scalable pipeline of innovative fragrance ingredients.

Key Responsibilities & Accountabilities

  • Support the design and optimization of novel fragrance molecules using computational chemistry, cheminformatics, and AI-based approaches.
  • Execute virtual screening, molecular modeling, and data analysis workflows to identify and prioritize promising molecular candidates.
  • Develop, apply, and continuously improve predictive models for molecular properties, fragrance-relevant attributes, and developability criteria.
  • Curate, analyze, and integrate chemical and biological datasets to improve model performance and discovery outcomes.
  • Collaborate with synthetic, analytical, biology, and fragrance research teams to support experimental validation and interpretation of results.
  • Contribute to the design and exploration of virtual molecular libraries to identify differentiated regions of chemical space.
  • Evaluate computational results and communicate insights clearly to multidisciplinary stakeholders.
  • Stay current with emerging AI, machine learning, and computational chemistry methodologies and help implement relevant innovations within the discovery workflow.

What Makes You the Right Fit

  • PhD in Computational Chemistry, Cheminformatics, Data Science, Chemistry, Chemical Engineering, Computational Biology, or a related scientific discipline.
  • +3 years of experience in computational chemistry, AI-driven molecular design, cheminformatics, or related fields, gained through academic research, internships, or industry experience.
  • Proven expertise in:
    • Structure-based and ligand-based modeling
    • Olfactophore/pharmacophore development and virtual screening
    • Physico-chemical property modeling and optimization
  • Solid understanding of:
    • Molecule - protein interactions (receptor biology)
    • Structure - function relationships (affinity, selectivity, activity drivers)
  • Hands-on experience with AI/ML approaches in chemistry, including generative models, predictive modeling, or data-driven design workflows, and ability to critically assess model performance and limitations.
  • Demonstrated ability to design and guide large-scale molecular libraries and explore chemical space efficiently to generate high-value candidates.
  • Strong scientific leadership and credibility, with the ability to operate as a peer to leading AI companies and influence external partners, while working effectively in highly interdisciplinary and fast-paced environments.

How You Would Stand Out

  • Experience developing machine learning or deep learning models for scientific applications.
  • Hands-on experience with generative AI approaches for molecular design.
  • Familiarity with cheminformatics platforms and molecular modeling software.
  • Exposure to fragrance science, receptor biology, medicinal chemistry, biotechnology, or related discovery fields.

Why Choose Us?

  • Opportunities to learn, develop, and expand your expertise across regions
  • Be exposed to global projects and participation in worldwide initiatives.
  • Receive competitive compensation and benefits package, including performance incentives.

We are a global leader in taste, scent, and nutrition, offering our customers a broader range of natural solutions and accelerating our growth strategy. At IFF, we believe that your uniqueness unleashes our potential. We value the diverse mosaic of the ethnicity, national origin, race, age, sex, or veteran status. We strive for an inclusive workplace that allows each of our colleagues to bring their authentic self to work regardless of their religion, gender identity & expression, sexual orientation, or disability.

Visit IFF.com/careers/workplace-diversity-and-inclusion to learn more

Company at a glance

At IFF, we make joy through science, creativity and heart. As the global leader in flavors, fragrances, food ingredients, health and biosciences, we deliver groundbreaking, sustainable innovations that elevate everyday products—advancing wellness, delighting the senses and enhancing the human experience.

With ~22,000 employees across 65 countries, more than 110 manufacturing facilities, 100 R&D centers and 33,000 customers worldwide, we turn possibilities into reality by redefining the limits of science and nature to create a more positive, sustainable future for all.

Visit us at www.iff.com to learn how our real-deal experts approach work with an entrepreneurial mindset, working lockstep to defy expectations and create industry-defining solutions that do more good for people and planet

Team Size10,001+ employees
WorkspaceOn-site
IndustryChemical Manufacturing
Location
Shanghai, Shanghai, China
Websiteiff.com
LinkedInLinkedIn

Top Benefits

  • Competitive compensation
  • Performance incentives

Tired of cold applications?

Sign up with Clera and we'll reach out the moment a role actually fits you — no more spraying applications into the void.

Know someone who'd be great for this?