--- title: 'Spring ’27 Intern – ML / Perception / Robotics at moss' canonical: 'https://feeny.ai/job/spring-27-intern-ml-perception-robotics-moss-san-francisco-azsbr0qsdnp1' type: 'job' last_seen: '2026-09-14' --- # Spring ’27 Intern – ML / Perception / Robotics at moss - **Company:** moss - **Location:** San Francisco, CA - **Employment:** internship - **Work type:** onsite - **Posted:** 2026-09-06 - **Last confirmed live:** 2026-09-14 - **Apply:** https://jobs.gem.com/moss-ag/am9icG9zdDqbIu-Bj_pR3QAv8YRyVo91 ## Job description ## About Us At [moss.ag](https://www.moss.ag/), we build robots to go where humans won't, digitizing the physical outdoor world to make it machine-readable. Starting with tree farms — where a single field holds millions of plants no human has ever fully inventoried. 🌲🤯🌳 We’re a small team of practical engineers with a long-term vision. We focus on real, messy, on-the-ground problems today, while working toward a future where autonomous field robots make harsh outdoor jobs easier and safer. If our mission aligns with how you work and think, we’d love to learn more about you! ## The Role Join us as an ML, Perception, or Robotics Intern on a fast-moving team building the systems that allow our robots to understand and operate in complex outdoor environments. Depending on your interests and experience, you may work on 3D perception, multimodal ML, sensor fusion, mapping, localization, navigation, or autonomy. You might train detection and segmentation models on large custom datasets, fuse LiDAR and camera data, build 3D mapping and localization systems, develop robot behaviors, or optimize models and algorithms for real-time deployment on edge GPUs. Our robots operate through changing light, harsh shadows, motion, dust, dense vegetation, uneven terrain, and severe occlusions. You’ll work across the full loop — from data and research to deployment, field failures, and iteration on real robots. We’re hiring for Spring 2027 internships, co-ops, and part-time roles, with the possibility of starting earlier part-time. ## Minimum Requirements - Impressive technical projects beyond the classroom in ML, computer vision, perception, robotics, mapping, or related fields - Strong programming skills in Python, C++, or Rust - Hands-on experience with at least one of the following:- Machine learning or computer vision - 3D perception, point clouds, or sensor fusion - Localization, mapping, navigation, controls, or robot behaviors - Comfortable working in Linux and debugging real systems - Excited to learn quickly, take ownership, and test your work on real robots - Experience with PyTorch, LiDAR, cameras, ROS, CUDA, model deployment, or edge computing is valuable but not required ## What You'll Do - Own projects from research and design through deployment and iteration on real robots - Build and evaluate ML, perception, mapping, and autonomy systems - Train models on custom outdoor datasets collected by our robots - Develop sensor fusion across LiDAR, cameras, GPS/IMU, and other sensors - Build localization, navigation, controls, and robot behaviors - Develop tools for data collection, labeling, training, evaluation, simulation, and field debugging - Optimize models and algorithms for latency, memory usage, and reliability on edge hardware - Test and deploy robotic systems during real-world customer operations - Collaborate closely with perception, software, electrical, and mechanical engineers ## About moss ## Company Overview - **One-liner**: Moss.earth is a climate tech company that develops and tokenizes carbon credits from Amazon Forest conservation and reforestation projects using blockchain, satellite imaging, and machine learning. - **Entity Type**: Private – Series A (raised $10M in Series A, total $13.4M in funding) - **Headquarters**: São Paulo, Brazil - **Founded**: 2020 - **Founders**: Camila Assis (Co-Founder & CMO) and Alexandre Lomaski (Co-Founder & CPO) ## Core Business - **Primary industry**: Carbon credits, carbon offsetting, environmental services, climate tech - **Target customers**: B2B (enterprises offsetting emissions), B2C (individuals compensating their footprint), and forest landowners - **Mission/purpose**: Use technology to protect the Amazon forest and help clients compensate their greenhouse gas emissions, becoming a global reference in the voluntary carbon market. ## Products & Services - **[MCO2 Token]**: The world’s first tokenized carbon credit listed on major global exchanges (Coinbase, Gemini). Each token represents one ton of avoided CO₂ emissions from Amazon forest conservation. - **[Moss Forest (DMRV Platform)]**: A Digital Monitoring, Reporting, and Verification platform that uses satellite imaging, big data, and machine learning to measure carbon stocks and monitor projects in real time. - **Carbon Credit Origination**: End-to-end project development including legal, land, and environmental evaluations for APD (Avoided Planned Deforestation), AUD (Avoided Unplanned Deforestation), ARR (Reforestation), and biochar projects. - **Corporate Carbon Offset Calculator**: B2B tool for companies to calculate and offset their 2023 (and forward) carbon footprint. - **Administrative Compensation Services**: Custom offset solutions for services, products, events, transportation, and cryptocurrency transactions. ## Market Standing - **Valuation/Market Cap**: Not publicly available - **Key Metric – Total Funding**: $13.4M (Seed round $1.6M in 2020, Seed round $1.8M in 2021, Series A $10M in Jan 2022) - **Notable Investors/Partners**: Acre Venture Partners, SP Ventures, The Craftory, Jive Software, Flori Ventures; Exchange partners include Coinbase, Gemini, and Regen Registry - **Growth Signals**: - Recognized as the 8th largest voluntary carbon credit transactor globally in 2021 - Named in *Environmental Finance* survey (2023) - Acquired OnePercent (a carbon offset platform) in 2021 - Expanded physical presence to Manaus, Brazil, and opened offices in Madrid (Spain) and Montevideo (Uruguay) - Great Place to Work® certified for three consecutive years - Employee count: ~7–12 (source variance); international team across Brazil, Uruguay, Spain ## Competitive Advantages - **First mover in tokenized carbon credits**: MCO2 remains the most widely listed tokenized carbon credit on major exchanges, providing liquidity and trust. - **Amazon-exclusive focus**: Deep expertise in the Amazon biome, with projects that deliver environmental co-benefits (biodiversity, habitat conservation). - **Proprietary DMRV platform**: Combines satellite imaging, process automation, and ML for accurate, verifiable carbon measurement, reducing certification costs and time. - **Blockchain-backed transparency**: Every credit is tracked on-chain, allowing users to verify the environmental impact and avoid double-counting. ## Strategic Focus - Expanding project types (especially biochar and reforestation in the Amazon) - Scaling geographic footprint in Latin America and Europe - Deepening Web3 integrations for carbon credit trading and DeFi applications - Strengthening partnerships with large enterprise clients for B2B offset programs - Continuing innovation in remote sensing and AI-driven forest monitoring ## Why Work Here - **Culture**: Small, agile team (under 15 people) with a mission-driven focus on climate action. Rated 3.9/5 on employer review sites, with particularly high marks for compensation (4.3) and work-life balance (4.1). - **Great Place to Work®**: Certified for three consecutive years (2022–2024), indicating strong internal culture. - **International exposure**: Offices in Brazil, Spain, and Uruguay; remote/hybrid options are likely given the distributed team structure. - **Impact**: Directly contributing to Amazon conservation and global carbon markets – a tangible climate impact. - **Tech stack**: Works with blockchain, satellite imagery, big data, and ML – appealing for engineers interested in climate tech. - **Note on Careers Page**: The provided careers link (jobs.gem.com/moss-ag) appears to correspond to a separate company (a farm robotics startup, Moss.ag). For Moss.earth-specific roles, candidates should visit moss.earth or its LinkedIn page. ## Sources 1. [moss.earth (official)](https://moss.earth) 2. [LinkedIn – Moss.earth](https://linkedin.com/company/moss-earth) 3. [Climate Tech List – Moss.earth profile](https://www.climatetechlist.com/company/mossearth) 4. [Tracxn – MOSS company profile](https://tracxn.com/d/companies/moss/__zG9J8_QTDvk3a-_kMgiETB9kGy_-mi_8ofN_vqcXS7Q) 5. [Gem Careers – Moss.ag (separate entity)](https://jobs.gem.com/moss-ag) ## Other roles at moss - [Summer '27 Intern - Electrical Engineering](https://feeny.ai/job/summer-27-intern-electrical-engineering-moss-san-francisco-ny3ptdmxgfwq) — San Francisco, CA - [Summer '27 Intern - Mechanical Engineering](https://feeny.ai/job/summer-27-intern-mechanical-engineering-moss-san-francisco-mpsy9v38ftwy) — San Francisco, CA - [Sales Lead](https://feeny.ai/job/sales-lead-moss-san-francisco-36dzzt31wfz5) — San Francisco, CA - [Fall '26 Intern - Perception/Robotics](https://feeny.ai/job/fall-26-intern-perception-robotics-moss-san-francisco-69xhgkyn9fvs) — San Francisco, CA - [Field Operator](https://feeny.ai/job/field-operator-moss-boring-m0kpgbxwm15p) — Boring, OR - [Spring '27 Intern - Mechanical Engineering](https://feeny.ai/job/spring-27-intern-mechanical-engineering-moss-san-francisco-x2fw2jxtzkzx) — San Francisco, CA - [Spring '27 Intern - Electrical Engineering](https://feeny.ai/job/spring-27-intern-electrical-engineering-moss-san-francisco-n05y4cysp1cp) — San Francisco, CA - [Perception Engineer](https://feeny.ai/job/perception-engineer-moss-san-francisco-f5e7013znn4p) — San Francisco, CA