What are the responsibilities and job description for the Cognitive Analytics Engineer position at Corteva Agriscience?
At Corteva Agriscience, you will help us grow what’s next. No matter your role, you will be part of a team that is building the future of agriculture – leading breakthroughs in the innovation and application of science and technology that will better the lives of people all over the world and fuel the progress of humankind.
This role is central to our cognitive analytics strategy: you'll help build and deploy the agentic systems and digital twin environments that enable teams to seamlessly integrate simulation, reinforcement learning, and AI-powered decision tools into breeding pipelines and workflows. You'll partner with scientists and engineering stakeholders to deploy these systems to our breeding teams across crops and geographies.
Who You Are
You're a systems-minded AI engineer who thinks natively in terms of agents, environments, and optimization. You're comfortable building the infrastructure that makes agentic workflows reliable and scalable, and you have the theoretical grounding to reason about reinforcement learning formulations, simulation fidelity, and reward design. You thrive in collaborative, cross-disciplinary teams and can translate between ML research and production engineering.
What You'll Do
Corteva Agriscience is an equal opportunity employer. We are committed to embracing our differences to enrich lives, advance innovation, and boost company performance. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, military or veteran status, pregnancy related conditions (including pregnancy, childbirth, or related medical conditions), disability or any other protected status in accordance with federal, state, or local laws.
- Please note: there is no visa sponsorship provided for this role.
This role is central to our cognitive analytics strategy: you'll help build and deploy the agentic systems and digital twin environments that enable teams to seamlessly integrate simulation, reinforcement learning, and AI-powered decision tools into breeding pipelines and workflows. You'll partner with scientists and engineering stakeholders to deploy these systems to our breeding teams across crops and geographies.
Who You Are
You're a systems-minded AI engineer who thinks natively in terms of agents, environments, and optimization. You're comfortable building the infrastructure that makes agentic workflows reliable and scalable, and you have the theoretical grounding to reason about reinforcement learning formulations, simulation fidelity, and reward design. You thrive in collaborative, cross-disciplinary teams and can translate between ML research and production engineering.
What You'll Do
- Build and maintain agentic AI systems that orchestrate analytics, simulation, and decision workflows for breeding pipelines, guiding solutions from prototype through production deployment
- Implement and optimize digital twin components for use with agentic inference systems and reinforcement learning training pipelines
- Develop and train reinforcement learning agents that optimize breeding pipeline strategy
- Collaborate with scientists and domain experts to address breeding challenges with agentic-driven solutions leveraging simulation and deterministic optimization
- Architect for scale and deployment — distributed training, efficient orchestration, and production-grade reliability of AI systems
- Master's degree in computer science, machine learning, or a related field (or equivalent practical experience), with 3–5 years of relevant experience
- Strong Python skills with computational and scientific libraries
- Experience with deep learning frameworks (e.g. PyTorch, JAX)
- Experience with reinforcement learning frameworks and theory
- Experience with simulation environments or digital twin systems
- Experience with deployment of orchestrated agents and associated components (e.g. MCP, ACP)
- Experience with distributed training and efficient AI orchestration
- Strong communication skills — able to bridge AI/ML concepts with domain scientists and cross-functional teams
- Experience with Linux and Docker
- Experience with LLM-based agent architectures, tool-use orchestration, or multi-agent systems
- Experience designing or building custom reinforcement learning environments for real-world decision problems
- AWS/Kubernetes experience
- Experience with compiled languages (e.g. C , Rust) for performance optimization
- Background in plant breeding, genetics, agriculture, or related domains — candidates with reinforcement learning and simulation backgrounds in other complex decision domains (robotics, operations research, autonomous systems) are encouraged to apply
- Numerous development opportunities offered to build your skills
- Be part of a company with a higher purpose and contribute to making the world a better place
- Health benefits for you and your family on your first day of employment
- Four weeks of paid time off and two weeks of well-being pay per year, plus paid holidays
- Excellent parental leave which includes a minimum of 16 weeks for mother and father
- Future planning with our competitive retirement savings plan and tuition reimbursement program
- Learn more about our total rewards package here - Corteva Benefits
- Check out life at Corteva! www.linkedin.com/company/corteva/life
Corteva Agriscience is an equal opportunity employer. We are committed to embracing our differences to enrich lives, advance innovation, and boost company performance. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, military or veteran status, pregnancy related conditions (including pregnancy, childbirth, or related medical conditions), disability or any other protected status in accordance with federal, state, or local laws.