We are looking for a Trainee Embedded Vision Integration Engineer to join our sensor integration team and work alongside a Senior Engineer on precision turret systems for defense applications.
This is a hands-on technical role — not an internship with slides and reports. From day one you will assist with real hardware bring-up, camera integration, pipeline testing, and calibration tasks. You will learn by doing: reading real device datasheets, running GStreamer pipelines on NVIDIA Jetson, and debugging sensor output under actual field constraints.
If you have a solid foundation in C++ and Linux, genuine curiosity about embedded systems and computer vision, and want to grow fast in a defense-critical environment — this role is for you.
What We Offer
- Direct involvement in real defense projects for Ukraine — no toy tasks, no simulated environments.
- Mentorship from a Senior Embedded Vision Integration Engineer with hands-on daily guidance.
- Fast growth path: structured onboarding, real ownership of subtasks from month one.
- Exposure to the full embedded stack: hardware, drivers, pipelines, and system integration.
- Competitive trainee compensation with clear performance-based review milestones.
- Temporary military service exemption for the duration of work on defense-critical projects.
Requirements
Technical Background — Required
- Degree in progress or completed in Computer Science, Electrical Engineering, Physics, or similar.
- Working knowledge of C++ (C++11 minimum); comfortable writing and reading real code, not just tutorials.
- Linux command-line confidence: navigating the filesystem, running processes, reading logs, using ssh.
- Python scripting for basic automation and data processing tasks.
- Understanding of what a camera pipeline is — even at a conceptual level (capture → process → output).
- Ability to read technical documentation in English: datasheets, API references, driver guides.
- Readiness to work in a fast-paced, hardware-in-the-loop environment with real deadlines.
Will Be a Plus
- Any hands-on experience with cameras: USB webcam, CSI camera, IP camera — even in a hobby or university project.
- Familiarity with OpenCV — even basic image processing (read, resize, threshold).
- Exposure to GStreamer, V4L2, or RTSP streams — any level of familiarity.
- Experience with NVIDIA Jetson, Raspberry Pi, or any ARM-based Linux board.
- Basic understanding of computer vision concepts: image formation, color spaces, resolution vs. FOV.
- ROS or ROS2 exposure — even from a course or personal project.
- Any experience with sensor data: reading output from a rangefinder, IMU, or GPS module.
- Participation in robotics clubs, hackathons, or embedded systems competitions.
Responsibilities
- Assist the Senior Engineer with camera and sensor bring-up: connecting hardware, checking output, validating signal integrity.
- Location: our hardware lab and team are based in Kharkiv. We expect on-site presence — relocation support can be discussed.
- Run and modify GStreamer pipelines under supervision — test latency, diagnose frame drops, validate stream parameters.
- Support camera calibration workflows: capture calibration frames, run calibration scripts, verify results.
- Write and maintain test scripts in Python to automate sensor validation and regression checks.
- Document integration steps, hardware configurations, and test results in Confluence.
- Assist with sensor-to-sensor alignment tasks — follow established procedures and report anomalies.
- Support field testing preparation: pack and configure hardware, validate pipelines before deployment.
- Reproduce and isolate bugs reported from field tests — provide structured debug logs to the Senior Engineer.
- Research component datasheets, driver documentation, and integration notes as assigned.
- Gradually take ownership of defined subtasks as skills and context grow.
What We Expect From You
- Intellectual honesty: say what you know, flag what you don't, ask early rather than late.
- Structured thinking: when you hit a problem, describe what you tried, what you observed, and what you think the cause is.
- Ownership mindset: a trainee who asks "is there anything else I can do?" beats one who waits for the next task.
- Consistency over brilliance: we value engineers who show up, deliver, and communicate — every day.
