Senior ML Researcher: Domain-Aware Modeling for Agriculture

Bayer CropScience Limited; Tulsa (OK); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health care

Vision

Dental

Retirement

PTO

Sick leave

Job summary

Bayer Crop Science is seeking a Sr. Machine Learning Researcher to build domain-aware models for agriculture, blending biology, genomics and environment data.

You will craft interpretable AI architectures that leverage genetics, crop physiology and environmental dynamics to drive genomic selection and genome editing targets. The role requires a PhD and strong ML foundations, with experience in PyTorch/JAX or TensorFlow and collaboration across disciplines.

Qualifications

• PhD in ML, applied math, computational science or related field with deep modeling.
• Publications or thesis work in scientific ML or data-driven modeling.
• Proficiency with PyTorch, JAX or TensorFlow and scientific computing libraries.
• Experience with agentic AI concepts and multi-agent systems is a plus.

Responsibilities

• Design and validate domain-aware ML models for agriculture and genomics.
• Develop physics-inspired losses and constraints for reliable predictions.
• Enable genomic selection and genome editing target identification.
• Provide uncertainty quantification for decision-makers.
• Collaborate with interdisciplinary teams to translate biology into models.
• Transition prototypes into production-grade models in pipelines.

Skills

Strong collaboration

Excellent communication

Problem solving

Education

PhD in Machine Learning / related quantitative discipline

Tools

PyTorch

JAX

TensorFlow

Gaussian processes

Job description

Bayer Crop Science is seeking a Sr. Machine Learning Researcher to build domain-aware models for agriculture, blending biology, genomics and environment data.

You will craft interpretable AI architectures that leverage genetics, crop physiology and environmental dynamics to drive genomic selection and genome editing targets. The role requires a PhD and strong ML foundations, with experience in PyTorch/JAX or TensorFlow and collaboration across disciplines.