Deep Learning Engineer
Carbon Robotics•Seattle, WA
•$140,000 - $220,000•Onsite
About The Position
As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning systems that power our autonomous laser weeding robots in the field.
Requirements
- 2-4 years of professional experience designing and implementing novel deep learning architectures for production computer vision systems
- Deep understanding of foundational deep learning mathematics and the ability to apply first-principles thinking to architecture decisions
- Hands-on experience working across the software stack, including sensor integration and web services, ideally within a robotics or autonomous field equipment platform
- Experience with deep learning frameworks, particularly PyTorch, and proficiency in C++ for performance-critical model development and deployment
- Proven track record taking ML projects from inception through business impact — including data strategy, pipeline development, experimentation, and deployment at scale
- Strong expertise in modern object detection techniques (vision transformers, anchor-free detectors, embeddings, and beyond)
- Experience in autonomous driving or ADAS is a plus — background in perception pipelines, sensor fusion, or real-time inference in outdoor or unstructured environments is highly valued
- Comfort navigating ambiguity and making principled technical decisions in rapidly evolving technical landscapes
- Strong verbal and written communication skills — able to explain complex model behavior and tradeoffs to non-technical staff and customers
- Experience mentoring engineers and contributing to team technical culture
- 2-7 years of experience in deep learning model optimization and deployment
- BS+ in Computer Science, Machine Learning, or a related field (or equivalent experience)
Nice To Haves
- Experience in autonomous driving or ADAS is a plus — background in perception pipelines, sensor fusion, or real-time inference in outdoor or unstructured environments is highly valued
Responsibilities
- Lead the design and execution of experiments to develop and validate novel deep learning architectures for computer vision in agricultural environments
- Own model optimization and deployment pipelines — ensuring high performance, reliability, and scalability across operational field deployments
- Drive end-to-end ML workflows from data strategy and pipeline design through evaluation and production deployment
- Define best practices for experimentation, documentation, and model evaluation within the team
- Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact features
- Mentor and provide technical guidance to mid-level and junior engineers
- Communicate model architecture decisions, tradeoffs, and performance results to both technical and non-technical audiences
Benefits
- Competitive salaries
- Pre-IPO Stock Options
- Fully-paid medical, dental, and vision insurance premiums for you and all dependents
- Choice of PPO or HDHP/HSA
- Virtual Care - Doctor on Demand
- Employee Assistance Program
- Mental Health HRA
- Restricted Healthcare Travel support
- Menopause Support
- Life Insurance
- Long Term Disability
- Flexible PTO
- 401(k) plan
- Pet Insurance
- Commuter Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
