Platform Engineering Apprentice - Linux

About OriginOrigin is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver 5x faster execution, 250%+margin expansion, and significant cost savings. Join India's most talent-dense robotics team consisting of individuals from IITs, Stanford, UCLA, and more.

About the RoleOrigin Autonomy is looking for an early-career engineer to join our platform team as an apprentice. You'll work alongside senior engineers on embedded Linux systems, networking, robotic middleware, and cloud-connected services that keep our robots running on live construction sites. This role is built for someone with strong fundamentals and a real hunger to learn. We care more about how you think and how quickly you pick things up than about how many tools you've used.

What You'll Do• Help build and debug robot boot-up sequences and service orchestration, learning how to make system bring-up reliable and deterministic.

• Configure and troubleshoot Linux networking (TCP/IP, DHCP, DNS, iptables) for robot-to-cloud and inter-robot
  communication, under the guidance of senior engineers.
• Build, run, and maintain Docker containers for robot and cloud deployments.
• Write bash and Python scripts for fleet diagnostics, log collection, and routine system tasks.
• Work with the robotics, perception, and application teams to debug integration issues on real hardware.
• Follow team Git workflows and participate actively in code reviews, both giving and receiving feedback.
• Document what you build and learn so the rest of the team benefits.

Requirements
All candidates must show solid, hands-on competency in every item below. Expect each one to be tested in the interview.

• 0–1 years of experience, with at least one internship or ~6 months of hands-on work experience in software or systems engineering (full-time roles, internships, or research lab work all count).
• Linux systems programming in C, including file I/O (read, write, seek, mmap), multi-threading (pthreads, mutexes, condition variables), and socket programming (TCP/UDP, select/poll/epoll).
• C++ (C++14/17), including OOP, STL containers and algorithms, RAII, and smart pointers.
• Networking fundamentals: TCP vs. UDP, ARP, DHCP, DNS, IP addressing and subnetting, and how to debug connectivity with tools like ip, ping, ss, tcpdump, and iptables.
• Docker: writing Dockerfiles, using docker-compose, managing images and volumes, and debugging running containers.
• Core data structures and algorithms (stack, queue, heap, linked list, hash map) and the ability to reason about time and space complexity.
• Python and Bash scripting for automation and diagnostics.
• Git from the command line: branching, merging, rebasing, and resolving conflicts.
• Strong comfort on the Linux command line: processes, systemd services, permissions, and logs.
• Ability to learn independently by reading man pages, documentation, datasheets, and RFCs.
• No degree required. We evaluate on demonstrated skill, projects, and work experience.

Good to Have• Exposure to ROS 2 (pub/sub, services, actions, launch files) or DDS.

• Familiarity with CMake (targets, find_package, CTest).
• Understanding of P2P vs. centralized messaging (e.g. DDS vs. MQTT).
• Network configuration on routers and switches, including VLANs.
• Basic knowledge of SQL or NoSQL databases.
• Basics of network security: checksums and hashes (CRC, SHA), public-key encryption, and digital signatures.
• Projects on embedded hardware (Jetson, Raspberry Pi) or self-hosted servers and home networks.
• Open-source contributions or a GitHub profile showing systems-level work.

What You'll Get• Close mentorship from senior platform and robotics engineers, with regular code reviews and 1:1s.

• Real ownership of production systems running on robots deployed on live construction sites.
• Broad exposure across embedded Linux, networking, middleware, and cloud infrastructure.
• A fast-paced startup environment at the forefront of robotics and AI.
• A clear path to a full-time Platform Engineer role based on performance.