We support our customers completely, we accomplish great things as a team, we are passionate about enabling a cleaner future for everyone, we act like owners, diversity in all that we do is our strength, success comes because we are great learners, we are persistent and forthright and realistic, and our optimistic nature allows us to take on any challenge.
In this role, you will:
Deploying computer vision models into an edge environment – Nvidia or similar platforms.
Involvement in all aspects of annotating, training, testing, iterating, and production monitoring of ML models for vision-based tasks.
Developing algorithms for speed, accuracy, and robustness to production operating conditions.
Developing operating procedures for data collection to optimize model quality.
Making critical architecture decisions based on benchmarking results.
Skills & Experience
At least 2 years of experience developing computer vision applications using Python, C++, and/or related tools.
Experience in developing, training, optimizing deep neural networks for real-time detection on embedded systems using one or more deep learning frameworks such as Pytorch, Tensorflow, Darknet, etc.
Experience in deploying computer vision models into an edge computing environment. Platforms such as Nvidia.
A combination of formal education and demonstrated application of Computer Vision.
Interest in agricultural applications and agrotechnology.
Excellent communication skills. A friendly-but-relentless approach to work. This exciting work is inherently multidisciplinary and requires the ability to work with people from a wide range of skills and domains of expertise.
Desired skills
Experience in deploying computer vision models in production.
Specific experience with object detection and image segmentation models and edge computing is an advantage.
Masters or Ph.D. in a relevant field is beneficial, but not required.
Experience with agricultural systems and/or models.
Familiarity with cloud computing platforms such as Amazon Web Services.
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