Machine Learning Engineer

Corteva

  • Hyderabad, Telangana
  • Permanent
  • Full-time
  • 1 month ago
DescriptionPosition : Machine Learning Engineer
Location: Hyderabad, India / FlexibleAbout Us 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 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.Responsibilities: 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 baremetal 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.
  • Automate and streamline ML operations and processes.
  • Build and maintain tools for deployment, monitoring, and operations. Also troubleshoot and
  • resolve issues in development, testing, and production environments
  • Experience in optimizing Machine Learning application for a target architecture is a plus
  • Team player with ability to work across a diverse team, also cross-functionally and in geographically distributed teams.
  • Meet the needs of Data Scientists, ML Engineers and provide mentorship to junior team members
QualificationsEducation and Experience
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science/Analytics or related field.
  • 3+ years of industry experience working in Software Engineering, DevOps or Data Engineering with Data Science and MLOps experience.
  • Good hands-on experience with containerized orchestration tools like Kubernetes
  • Experience in building and deploying applications in Cloud environment like AWS or GCP.
  • Proficiency in any one language like Python, R or any other programming languages
  • Experience with working on AWS services (S3, RDS, EC2, EBS, SQS, Lambda)
  • Experience in converting plain python models into deployable REST services using any frameworks (Seldon-Core / Kfserving etc.)
  • Experience with Pytorch, Tensorflow, Caffe2 or relevant frameworks will be an added advantage
  • Superior written communication and presentation skills.
  • Hands-on experience building the end-to-end design, development, and deployment of modelling solutions.
  • Experience working with Docker images and maintaining docker-based micro services.

Corteva

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