Role Overview
We’re looking for a Software Engineer to help build and maintain the software that powers our computer vision and AI solutions in production. You’ll work across the stack that gets our models from a training run to reliably running on hardware inside a live facility - handling data validation, deployment, monitoring, and everything in between.
You’ll work closely with our robotics, AI, and software engineering teams to deliver end-to-end solutions, and you’ll get hands-on exposure to the full model lifecycle: preprocessing, fine-tuning, evaluation, deployment, and monitoring. It’s a strong seat for an engineer who wants real ownership and to learn quickly on a small, senior team.
What You'll Do
- Develop and maintain software applications primarily using Python.
- Squeeze every millisecond out of inference by optimizing for edge hardware running on-site.
- Assist in model deployment across development, testing, and production environments.
- Perform input data validation, preprocessing, and quality checks to ensure reliable model performance.
- Debug and troubleshoot software, model inference, and system integration issues.
- Support model fine-tuning, evaluation, and performance optimization.
- Collaborate with robotics, AI, and software engineering teams to deliver end-to-end solutions.
- Document technical designs, implementation details, and troubleshooting procedures.
What We’re Looking For
- Bachelor’s degree in Computer Science, AI/ML, or a related field.
- Strong programming skills in Python.
- Understanding of software development fundamentals, data structures, and algorithms.
- Good debugging and problem-solving abilities.
- Familiarity with version control systems such as Git.
- Basic understanding of machine learning concepts and model lifecycle.
- Ability to learn quickly and work in a collaborative environment.
Bonus Points For
- Exposure to computer vision libraries such as OpenCV.
- Knowledge of machine learning frameworks such as PyTorch or TensorFlow.
- Understanding of model training, validation, deployment, and monitoring.
- Experience working with Linux environments.
