Carbon Robotics is the leader in physical AI for agriculture, helping farmers become more profitable and sustainable. Its flagship product, the LaserWeeder™, is the world’s leading commercial laser weeding system with hundreds of units operated by farmers in 15 countries worldwide.
LaserWeeder combines computer vision, AI, robotics, and high-powered lasers to identify weeds and destroy them with sub-millimeter precision—no herbicides, hand labor, or soil disturbance required. Growers achieve weed control cost reductions of up to 80% and crop yield increases of 5–50%, with payback in one to three years. The system is powered by Carbon AI’s Large Plant Model (LPM), trained on 150 million labeled plants, and can start weeding any crop or field in minutes.
The company's second product is Carbon Autonomy, the most dependable tractor autonomy solution. Carbon Autonomy includes a retrofit tractor autonomy kit for John Deere tractors, autonomy software, and remote supervision for real-time interventions if required.
Carbon Robotics is based in Seattle, Washington State, USA and has raised $185 million in capital since 2018 from leading investors including NVIDIA’s NVentures and BOND.
YouTube | X | Instagram | LinkedIn | News
Deep Learning Engineer
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.
What You'll Do
- 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
Knowledge, Skills & Abilities
- 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
Requirements
- 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)
In Office Requirements
- We're a collaborative, in-person team — this role is based in our Seattle office with at least 4 days per week on-site
Carbon Robotics follows equitable hiring practices. Flexibility in our hiring process allows hiring of talent at levels different from what are posted. The compensation range outlined is based on a target budgeted base salary. Individual base pay depends on various factors such as relevant experience and skill, Interview assessments and responsibility of role, job duties/requirements. Offers are determined using our equitable hiring practices. Carbon Robotics offers additional compensation in the form of benefits premiums, pre-IPO stock options and On Target Earning commissions for appropriate positions. Base pay ranges are reviewed each year. We are committed to the principle of pay equity – paying employees equitably for similar work.
Why would you join Carbon Robotics?
Passion for building teams capable of solving uniquely interesting problems. Innovation while disrupting the market is what we do. Profiled in WSJ and Forbes, Carbon Robotics is poised to become the next billion dollar company in the rapidly growing worldwide Ag-Tech industry.
We offer competitive compensation and benefits to our full time US based* employees, including:
- 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
- Fully-paid medical, dental, and vision insurance premiums for you and all dependents
- 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. This is the foundation to which we will build a truly unique environment.
We are equally committed to equal employment opportunity, and it is foundational to how we recruit and hire our talented team. Employment is determined based upon capabilities and qualifications without discrimination on the basis of race, creed, color, religion, sex, gender identification and expression, marital status, military status or status as an honorably discharge/veteran, pregnancy (including potential pregnancy, pregnancy-related conditions, and childbearing), sexual orientation, age (40 and over), national origin, ancestry, citizenship or immigration status, physical, mental, or sensory disability , HIV/AIDS or hepatitis C status, genetic information, status as an actual or perceived victim of domestic violence, sexual assault, or stalking, or any other protected class as established by law.
#talentacquisition #laserweeding #laserweeder #weedcontrol #agtech #agtechnology #farmtech #robotics #lasers #lasersandrobots #missiondriven #AI #startup #wearehiring #computervision #machinelearning #carbonrobotics
Carbon Robotics Seattle, Washington, USA Office
Belltown neighborhood with easy commuter access and parking.
Similar Jobs at Carbon Robotics
What you need to know about the Seattle Tech Scene
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
