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About the Role

Develop practical AI, machine learning, and optimization solutions to make complex industrial data easier to understand, explore, and act on. Apply frontier AI models, including large language models, foundation models, and multimodal approaches, to create reliable tools for search, analysis, knowledge discovery, and decision support. Build AI-enabled applications that combine models, data pipelines, prompts, agents, evaluations, optimization logic, and user feedback into useful, explainable, and maintainable solutions. Design and use knowledge graphs, ontologies, and structured domain knowledge to connect process data, experimental data, documents, terminology, assets, materials, and business context. Work with domain experts to translate scientific, engineering, process control, and operational questions into data products, model workflows, optimization approaches, and user-friendly analytics experiences. Develop robust pipelines for structured and unstructured data, including time-series data, laboratory data, manufacturing data, documents, and scientific or technical knowledge sources. Contribute to model validation, monitoring, documentation, governance, and continuous improvement so that deployed solutions can be trusted in real industrial environments. Collaborate across data science, engineering, digital technology, operations, and business teams to deliver solutions that create measurable value and are designed for adoption.

Responsibilities

Develop practical AI, machine learning and optimization solutions
Apply frontier AI models to create reliable tools for search, analysis, knowledge discovery, and decision support
Build AI-enabled applications that combine models, data pipelines, prompts, agents, evaluations, optimization logic, and user feedback
Design and use knowledge graphs, ontologies, and structured domain knowledge
Work with domain experts to translate scientific, engineering, process control, and operational questions into data products, model workflows, optimization approaches, and user-friendly analytics experiences
Develop robust pipelines for structured and unstructured data
Contribute to model validation, monitoring, documentation, governance, and continuous improvement
Collaborate across data science, engineering, digital technology, operations, and business teams to deliver solutions

Requirements

Master’s, or PhD degree in Chemical Engineering, Biochemical Engineering, Bioinformatics, Process Control, Computer Science, Data Science or Applied Mathematics
Demonstrated industrial experience with a proven track record of delivering measurable business impact and driving outcomes in production or operational environments
Proven, hands-on experience with Python and modern machine learning workflows
Experience developing end-to-end AI or machine learning applications
Practical understanding of frontier model capabilities and limitations
Experience working with structured and unstructured data
Knowledge of methods such as mathematical optimization, process control, forecasting, anomaly detection, recommendation systems, natural language interfaces, classification, deep learning, or predictive analytics
Familiarity with software engineering practices
Ability to communicate clearly with both technical and non-technical audiences
A practical, delivery-oriented mindset with curiosity for industrial, scientific, optimization, and process control problems and a strong focus on usefulness, trust, and adoption

Skills

Python
Machine learning workflows
Data preparation
Modeling
Validation
Deployment
Monitoring
AI
Machine learning
Large language models
Foundation models
Multimodal approaches
Prompt design
Agentic AI
Retrieval-augmented generation
Evaluation
Hallucination reduction
Human-in-the-loop workflows
Time-series data
Scientific data
Engineering data
Documents
Knowledge bases
Operational datasets
Mathematical optimization
Process control
Forecasting
Anomaly detection
Recommendation systems
Natural language interfaces
Classification
Deep learning
Predictive analytics
Version control
Testing
Application programming interfaces
Containers
Continuous integration
Continuous delivery
Maintainable code design
Knowledge graphs
Ontologies
Semantic modeling
Graph databases
Model registries
Experiment tracking
Observability
Prompt management
Version management
Evaluation frameworks
Cloud platforms
Production machine learning systems

Location

Remote

Work Type

Remote
Full-time

Experience Level

Industrial experience
Hands-on experience

Education Level

Master’s degree
PhD degree

Salary/Compensations

$100,000 - $120,000

Benefits

Medical
Dental
Vision
401k
Vacation
Holidays
Paid parental leave (maternity and paternity)
Annual bonus plan

About the Company

IFF is a global leader in flavors, fragrances, food ingredients and health & biosciences, delivering sustainable innovations that elevate everyday products.
Health & Biosciences: Channeling our passion for nature and bioscience into sustainable, life-enhancing technologies that power innovative solutions across healthcare, food, consumer and industrial markets.
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 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.

Equal Opportunity

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.
We value an inclusive, creative workplace where all individuals can thrive and do their best work.
We consider all qualified candidates equally and based on merit, without regard to religion, ethnicity, national origin, race, age, veteran status, gender identity or expression, sexual orientation or disability.