Platform Engineering Apprentice - Linux

About Origin
Origin 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 Role
Origin 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.