Verne Robotics is building intelligent robotic arms that can learn new skills in hours, not months. Backed by Y Combinator and top-tier Silicon Valley investors, we’re turning physical AI into reality — helping industries facing critical labor shortages (manufacturing, logistics, and more) automate back-of-house tasks like packaging, kitting, and folding.
Our flagship platform combines affordable robotic hardware with cutting-edge imitation learning algorithms, enabling reliable, sample-efficient robots that deliver customer value from day one. We’re already live with pilot partners and scaling fast. The founding team brings experience from Apple, Stanford, and Microsoft, with deep expertise in robotics, embodied AI, and large-scale machine learning.
We’re looking for a talented Robotics Software Engineer to design and build the core systems that power Verne’s robots in the real world. This is a hands-on role where your work will directly translate to physical robots performing customer-critical tasks. You’ll work across the full robotics software stack, from low-level sensor and actuator interfaces, to deploying large-scale policy learning pipelines, to shipping reliable features that customers depend on. Beyond just writing code, you’ll help design solutions, lead engineering efforts, and think cross-functionally to bridge hardware, machine learning, and product requirements.
Build and optimize robotics software in Python and C++, spanning device drivers, control interfaces, and high-level APIs that power real-world deployments.
Integrate and deploy ML policies (PyTorch) into visuomotor control loops, ensuring efficient inference on edge hardware.
Design and test training pipelines for policy learning, including dataset preparation, augmentation, and scaling across massive multi-modal datasets (video, teleop trajectories, sensor streams).
Develop infrastructure for teleoperation and autonomy, including real-time data streaming, low-latency WebRTC systems, and fallback human-in-the-loop control.
Prototype new robot capabilities by collaborating closely with the hardware and research teams, translating experimental ideas into production-ready features.
Systematically evaluate and test policies through lab trials, and live customer POC. Measuring performance, robustness, and safety at scale.
Contribute to cloud + edge scaling efforts, including AWS-based data ingestion pipelines, IoT fleet management, and distributed training/serving infrastructure.
Take ownership of engineering projects end-to-end, from design discussions and architecture, to implementation, testing, and deployment in the field.
Work cross-functionally with product, research, and customer teams to ensure the systems you build align with real-world needs and unlock tangible customer value.
B.S., M.S., Ph.D. in computer science or related fields.
Strong programming skills in Python (you write clean, efficient, production-ready code)
Solid experience with PyTorch and modern ML workflows
Systems engineering skills (networking, concurrency, performance)
At least 3 years of full-time work experience for candidates with a B.S. in related fields. 1 years of experience for M.S. or Ph.D. candidates.
Experience with robotic arms, embedded systems, etc (e.g., Arduinos, motors, robot arms)
Preferred
Experience with real-time systems (cameras, sensors, streaming)
Hands-on with AWS services (EC2, IoT, WebRTC)
At Verne, you won’t just be writing code, you’ll be shaping the future of physical AI. You’ll see your work run on real robots, in real customer environments, with immediate impact. You’ll join a small, world-class team where your contributions matter and your growth is accelerated.
Location: South San Francisco, CA (on-site required)
Compensation: Competitive salary + meaningful equity
Perks: Free meals vouchers, hardware access, health benefits, PTO
This is a rare chance to join a YC-backed robotics startup early and help build the foundation of the company. If you’re excited about robots, passionate about solving hard problems, and eager to see your work come alive in the real world — we’d love to hear from you.
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