Deep Learning Engineer

Deep Learning Engineer

The Carbon Robotics Laser Weeder™ leverages advanced robotics, computer vision, AI/deep learning, and lasers to eliminate weeds with sub‑millimeter accuracy—all without herbicides. This innovative solution reduces environmental impact, promotes soil health, and helps farmers address labor shortages and rising costs. Designed in Seattle and built at our cutting‑edge manufacturing facility in Richland, Washington, the Laser Weeder is setting a new standard for automated weed control.

• 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

• 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)

• We’re a collaborative, in‑person team — this role is based in our Seattle office with at least 4 days per week on‑site

Base pay ranges: $140,000—$220,000 USD.

• Competitive salaries
• Pre‑IPO Stock Options
• Generous Benefits:
  • 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
• Work Culture:
  Be a part of an inclusive and tight‑knit company culture that values innovation and mission‑driven success.
• Internationally based employees benefits varies & contractors are not eligible for Carbon Robotics Benefits or Stock

Carbon Robotics is building a culture of diversity and inclusion for all. We welcome everyone’s voice and believe in open and transparent communication. We believe the best products, services, and companies are built by strong teams that include a diversity of backgrounds, perspectives, ideas, and experiences. We are committed to supporting and enabling growth and opportunity for every employee at every level.

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