Research Software Engineer - Expert
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Research Software Engineer
We are looking for an individual to drive, build and deliver The Agronomic Intelligence Platform which can be leveraged by various data science and engineering organizations through Our Clients Digital Farming Platform (DFP) You will be responsible for Design and implement highly scalable data-intensive processing systems, highly scalable micro service-based services that can be put to use by various teams within the organization, as well as by partners,
As an Agronomic Intelligence Platform Engineer you will be responsible for designing and implementing APIS, SDKs and services.
As our client matures as a data company there is a need to author, create and manipulate models with varying inputs, performance SLA’s and workflows. Generally the model development life cycle starts with discovery after a few iterations of the internal logic developed independently by Science. Once the model matures enough or ready to be put to test against large volumes of data, then re-implemented by Engineering to conform to the requirements and restrictions of production processes and infrastructure. Development of new models, as well as ongoing maintenance of existing models, is labor-intensive, and requires extensive coordination between Engineering, Science.
You will be part of the team who is responsible to design and implement a platform that abstracts the lowest level of that ecosystem in a dynamic and generic manner so that Science (and potentially others) can publish and execute models in the production environment without/minimal the need for direct involvement of Engineering. Ultimately the platform should help accelerate the development of Agronomic Intelligence.
Desired Skills/ Experience
- BS in software related field or equivalent combination of education and experience
- Software engineering work experience using a functional or object oriented language (Java, Python, etc.)
- Experience building scalable backend services (REST APIs, micro services, designing and implementing efficient data processing algorithms, messaging paradigms, middleware, persistent store)
- Experience working with AWS or other public Cloud platforms
- Experience with building real-life data science projects.
- Solid knowledge of building large scale systems using Python.
- Excellent written and verbal communication, presentation, engineering diagrams, and listening skills with the ability to present complex technical information in a clear and concise manner
- Solid knowledge of software development methodologies and best practices
- Experience building robust backend services and REST APIs
- Experience with relational and non-relational databases and persistence store
- Experience with Amazon Web Services (EC2, S3, RDS, SQS, etc.) (Strong Plus)
- Knowledge of functional programming (Strong Plus)
- Experience with compiled JVM language (Java, Scala, Clojure) (Strong Plus)
- Knowledge of kubernetes
- Knowledge of Kubeflow or Metaflow