Machine Learning Scientist

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us.

If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Machine Learning Scientist

At Bayer Crop Science, you have the opportunity to transform how we steward innovation in plant breeding through the power of machine learning;
As a Machine Learning Scientist focused on Quality, Stewardship, and Compliance (QSC), you lead the development and execution of a strategic framework that enhances quality, compliance, and stewardship across Bayer Plant Breeding;
In this role, you drive high‑impact initiatives in close partnership with Global Stewardship representatives, ensuring alignment with organizational standards and regulatory expectations;
You collaborate extensively across functions and with ML, IT, and data stewardship teams to design and refine digital systems and analytical methods that streamline stewardship program management for Bayer Plant Breeding;
You develop innovative, data‑driven solutions and visualizations that strengthen program efficiency and promote consistent adoption of internal policies and external regulatory guidance.

The primary responsibilities of this role, Machine Learning Scientist, are to:

• Report to the Quality, Stewardship, and Compliance Lead;
• Design and implement scalable tools and services for machine learning training and inference while selecting suitable cloud and on‑premises infrastructure for production‑level machine learning models;
• Play a hands‑on role in building interpretable ML products while incorporating suggestions from plant breeders, laboratory experts, and stewardship experts;
• Support and develop data visualizations to streamline and improve efficiency of Bayer’s Plant Breeding pipeline;
• Query Bayer Crop Science data to provide support and insight for incident management and process improvements;
• Leverage ML techniques to optimize and automate current QSC processes;
• Proactively leverage data and build insights to identify opportunities within QSC workflows that improve delivery (cost, timeline, etc.) for Bayer’s Plant Breeding;
• Implement data quality checks, security measures, and governance standards to ensure accuracy and reliability.

An ideal applicant is internally driven and motivated by urgency as well as the potential of modernizing the stewardship, quality, and compliance area for Plant Breeding; brings hands‑on experience with product ionizing machine learning models; and is willing to speak out and provide insightful suggestions.

Bayer seeks an incumbent who possesses the following:

• Bachelor’s degree in a relevant field with strong grounding in Machine Learning, with an emphasis on plant breeding preferred;
• Demonstrated experience conducting research and contributing to research projects, technologies, publications, intellectual property, or trade secrets;
• Demonstrated experience with open‑source deep learning frameworks such as Tensor Flow and/or PyTorch, and strong competency in Python as a programming language;
• Demonstrated experience with large language models (LLMs) and retrieval‑augmented generation (RAG) approaches;
• Demonstrated experience with SQL and data visualization tools such as Spotfire and Power BI;
• Direct knowledge regarding the implementation of deep learning techniques, including Transformers;
• Experience with backend and API development;
• Experience and proficiency working with high‑dimensional data.

• Ph.D. with a minimum of 3 years of relevant experience;
• M.S. with a minimum of 5 years of relevant experience;
• B.S. with a minimum of 7 years of relevant experience.

Employees can expect to be paid a salary between $96,800-$145,00

Additional…