Project Description:
At Ceres, we’re building the world’s most advanced data analytics platform for agriculture. We believe the future of agriculture depends on building the right tools to help farmers, insurers, lenders, and sustainability partners make the most of their limited resources. We are a science-driven organization with a vision of sustainable agriculture that works for farmers.
Job Description:
In this role, you will collaborate with an international team of engineers, scientists, and analysts to develop and implement machine-learning/computer vision algorithms and techniques to analyze and interpret hyperspectral imagery from a variety of sources. Your expertise will contribute to improvements in data quality, increased automation throughout our production workflows, and more streamlined/efficient workflows as we continue to scale our business.
Responsibilities:
- Streamline existing workflows by increasing the accuracy of our image segmentation and tree counting models.
- Creatively apply machine learning techniques to remaining manual touchpoints in our workflow.
- Monitor the health of models over time and prioritize areas for improvement based on analysis and analyst feedback.
- Collaborate with engineers/scientists/analysts to incorporate new scientific ML-based products into our production pipelines.
- Troubleshoot production-related/operational issues in real time.
Requirements:
Required competencies:
- At least 3 years of relevant hands-on development experience
- Proficiency with Python as well as relevant CV/ML libraries: Tensorflow, OpenCV, PyTorch etc.
- Competence in computer vision techniques such as image processing, object detection, image segmentation, and feature extraction
- Familiarity with AWS Cloud-based (S3/EC2/EMR and Compute/Storage/Dataproc) tooling for data science and ML pipelines
- Familiarity with geospatial tools (QGIS, python-based raster processing libraries such as rasterio and geopandas)
- Strong communication skills — you’ll be collaborating with a variety of teams with differing technical backgrounds
- English language competency
Nice To Have:
- Experience building “end-to-end” machine learning solutions
- Experience with JupyterHub
- Understanding of photogrammetric processing
- DevOps experience or interest in learning
- Interest/experience with agriculture
Employee benefits:
- Comfortable office within walking distance of a metro station
- Flexible schedule: 8-hour work day with opportunity to work remotely
- Competitive salary and regular performance reviews
- Work closely with an international team
Are you a good fit? Send us your CV in English. We are waiting to hear from you!