TurbineOne is looking for a Machine Learning Engineer to design and develop machine learning systems and infrastructure for training and inference at the edge, and to ship production-grade machine learning features to TurbineOne's Front Line Perception system.
Requirements
- Experience in a production software development environment (version control, automated testing, build tools)
- Knowledge of deep learning algorithm development and experience with ML experimentation
- Experience with all or some of TensorFlow, PyTorch and Jax.
Responsibilities
- Designing and developing machine learning systems and infrastructure for training and inference at the edge
- Maintain and update the APIs between products and ML features to enable rapid iteration and adoption of new functionality
- Shipping production grade machine learning features to TurbineOne’s Front Line Perception system
- Building and integrating new data models and user interfaces for gathering user data to enable to new ML-based product solutions
- Creating and maintaining reusable functional blocks for machine learning models, such as data loading, inference batching, etc.
- Productionizing machine learning prototypes, papers and state-of-the-art architectures to solve product problems
- Maintain and improve existing TurbineOne machine learning frameworks and libraries
Other
- Geographically flexible for home-office
- High standard of ethics, grit, integrity and moral character
- Ability and confidence to learn what’s required to add functionality to the product, from the ML stack to the front end.
- College degree/certifications in Computer Science or similar field
- Deep curiosity about customer problems and technical solutions
- Positive and solution-oriented mindset
- Must be eligible to obtain a clearance with the U.S. government
