Who are we, and what do we do?
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.
Corteva Agriscience is seeking a Machine Learning Infrastructure Engineer to implement of our end-to-end ML pipeline by leveraging their deep knowledge of best practices in machine learning, data pipelines and large-scale distributed systems.
As part of our global Farming Solutions and Digital group, you’ll be working on developing and enhancing our core ML capabilities as applied to large-scale agricultural datasets in imaging, genomics, remote sensing, natural language processing, plant breeding, etc.
The successful candidate will work closely with data engineers, software engineers, ML engineers, and data scientists in a dynamic and exciting research environment to implement scalable machine learning solutions requiring collaboration with team members and key stakeholders. You will operate as a thought leader and visionary that will encourage and promote disruptive advances by enabling the implementation of state-of-the-art methods in machine learning and artificial intelligence. This is a critical position with strategic impact on our business and you will play a major role by driving innovation in agriculture technology.
Locations: USA or Canada (100% remote is an option)
How will you help us grow? It matters to us, and it matters to you!
- Design and implement production-grade, user-friendly infrastructure to run AI pipelines at scale including model development, model deployment, model serving, model monitoring and experimentation.
- Utilize best practices in DevOps and machine learning methods on cloud native computing architectures with an infrastructure-as-code approach using tools like Terraform and Git.
- Ensure complete utilization of our high-performance GPU and CPU computing assets on bare-metal and cloud environments (AWS, GCP, Azure) with emphasis on efficient resource management and cost effectiveness.
- Create reliable and reproducible workflows and pipelines that deliver data products to our end users.
- Meet the needs of Data Scientists, ML Engineers and provide mentorship and/or manage junior team members.
What expertise have you grown? What do you bring to the table?
Education and experience:
- M.S. in Computer Science, Software Engineering, Bioinformatics, Machine Learning, Artificial Intelligence or related quantitative discipline with at least 3 years of demonstrated experience.
- B.S. in related discipline with at least 5 years of demonstrated experience
- Foundational understanding of how machine learning, deep learning and AI algorithms work including end-to-end machine learning model lifecycle development from initial conception, model training, model serving and workflow tools to enable rapid and reliable ML experimentation at scale.
- Experience administering and maintaining Kubernetes cluster deployments on bare metal and cloud environments optimized for machine learning workloads with cloud native infrastructure patterns using modern DevOps, GitOps and CI/CD principles.
- Experience integrating and optimizing high-performance computing hardware such as InfiniBand, RDMA, AI accelerators (GPU, TPU, CPU, FPGA, ASICs), storage, multi-gigabit networking.
- Programming skills in Python, Go, Bash programming with the ability to quickly create prototype and debug solutions on Cloud Native / Linux / embedded platforms.
- Practical cloud computing experience with AWS, Azure, GCP technologies (virtual instances, object storage, container registries, IAM, etc.) utilizing infrastructure as code methodologies to create high performance and data intensive platforms
- Experience with machine learning libraries or frameworks such as KubeFlow, MLflow, Tensorflow, Keras, SciKit-Learn, PyTorch, Ray, TF Serving, Triton Serving, Seldon Core.
- Interest in learning new technologies, latest ML algorithms, programming techniques, languages, and operating systems.
- Excellent interpersonal skills and a can-do attitude with the ability to thrive in a fast-paced dynamic environment with attention to detail. Experience in research, agriculture, life sciences, or in data science is a plus.
- Strong verbal and written communication skills in English are required.
- Understanding of modern machine learning methods (convolutional neural networks/CNNs, generative adversarial networks/GANs, reinforcement learning paradigms and transformer networks) as applied to imaging, natural language processing, genomics or chemistry.
We care about you and we care that you’re comfortable. While there’s no place like home, Corteva comes close.
Let’s peek at how you can grow your wellbeing, health, and future at Corteva!
- Strike a better worklife balance with robust time off benefits including paid maternity, paternal and family illness leave
- Prepare for your future with our competitive retirement savings plan, tuition reimbursement program, and more
- Enjoy access to health benefits for you and your family on your first day of employment
- And much, much more!
Ready to grow your perspectives, impact and career? Start by applying to this opportunity today!