Job VC
Trainee Embedded Vision Integration Engineer
Technologies
Description
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.
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.