Jobs at DefTech companies

We are building a precision turret platform for the defense of Ukraine and are looking for a strong embedded engineer to own sensor integration and control logic - from hardware bring-up to field deployment.
 

What you'll do

• Integrate key sensors - LiDAR, thermal (IR) cameras, IMU - on edge platforms (NVIDIA Jetson, ARM).
• Implement and tune control and stabilization algorithms for turret movement and aiming.
• Apply applied mathematics in practice: coordinate transformations, filtering (Kalman), geometry, timing.
• Debug real hardware and support field testing of deployed systems.

What we're looking for

• 4+ years of embedded software development (Linux, C++).
• Hands-on experience with LiDAR and/or thermal camera integration.
• Solid math background: linear algebra, geometry, filtering.
• Experience with control algorithms, stabilization, or motion systems.
• Comfortable working close to hardware (UART/I2C/SPI/CAN) and making decisions independently.

Will be a plus

• Turrets, gimbals, drones, robotics, or other unmanned systems.
• Sensor fusion, target tracking, PID control.
• ROS2, GStreamer, OpenCV, edge AI pipelines.

What we offer

• Direct contribution to the defense of Ukraine - short path from code to field deployment.
• Ownership of architectural and integration decisions.
• Competitive compensation based on experience.
• Temporary military service exemption for work on defense-critical projects.

Vidar Systems is a Ukrainian startup in the field of acoustic technologies, operating at the intersection of defense and security. We develop acoustic systems that use sound to determine the location of hostile objects, including artillery and drones.

About the Role
Become a core member of our high-impact engineering team and architect the AI systems that protect Ukraine’s frontline defense. You will own the full lifecycle of ML solutions—from design to edge deployment—in a mission-critical acoustic reconnaissance environment.

What You’ll Do

• Design, implement, evaluate, and optimize ML/DL models for acoustic detection and classification tasks.
• Collect, clean, and preprocess datasets for model training and evaluation.
• Write modular, testable code for preprocessing, model inference, and automation tasks.
• Develop and maintain robust data pipelines to support efficient model training and evaluation workflows.
• Develop strategies for model quantization and compression to ensure high performance on resource-constrained hardware.

What You Need

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
• 2+ years of professional Python experience in ML/DL production applications.
• Hands-on expertise in designing, training, and integrating ML systems into production environments.
• Deep experience with TensorFlow, PyTorch, PyTorch Lightning, scikit-learn, NumPy, and Pandas.
• Strong analytical, communication, and problem-solving skills; ability to thrive and execute independently in a high-stakes, fast-paced startup environment.
• Good technical English.

Nice to Have

• C/C++ experience (especially valuable for our next-generation systems).
• Background in the audio domain or digital signal processing (DSP).
• Proficiency in training unsupervised learning models.
• Experience with the optimization and deployment of ML models on edge devices.

Our Recruitment Process

1. Intro call with recruiter — 45 min
2. Technical interview with ML Lead — 90 min
3. Test task — 4–6 hours
4. Final interview with ML Lead and CTO — 60 min

Why Join Us?

• High Autonomy: Shape the direction of our software solutions with minimal oversight and maximum ownership.
• Innovation at the Edge: Contribute to military acoustic reconnaissance systems at the forefront of defense tech, redefining ML in harsh, real-world acoustic environments.
• Flexible Work Options: Benefit from adaptable arrangements and a culture that truly values your input and well-being.

We are looking for a Middle Embedded Vision Integration Engineer to build and integrate camera, sensor, and video pipelines for UAV platforms operating under real-time, weight, and hardware constraints.

You will work on connecting cameras, gimbals, and onboard sensors into a cohesive embedded platform - from the companion computer to the flight controller - ensuring reliable, low-latency video and telemetry delivery to targeting, navigation, and ground control systems. This role is ideal for an engineer who already has solid embedded Linux experience and wants to grow into full integration ownership, working on hardware bring-up, driver configuration, and pipeline development under the guidance of senior engineers.

You will work directly on defense projects for Ukraine, with a short path from implementation to field testing.
 

What We Offer

• Direct contribution to defense projects for Ukraine.
• Mentorship from top experts in vision hardware, UAV systems, and embedded engineering.
• Hands-on involvement in integration and architecture decisions.
• Competitive compensation based on experience.
• Temporary military service exemption for work on defense-critical projects.
   

Requirements

Core Technical Skills - Required

• 3–5 years of commercial embedded software development.
• Degree in Computer Science, Electrical Engineering, Physics, or similar.
• Solid Linux embedded development experience (NVIDIA Jetson, Raspberry Pi, ARM SoCs as companion computers).
• Proficient in C++14/17; Python for tooling and scripting.
• Hands-on experience with at least one flight stack: ArduPilot, PX4, Betaflight, or INAV.
• Working knowledge of MAVLink and/or MSP protocols: telemetry, basic command & control.
• Hands-on experience with camera integration: MIPI CSI, USB3, or RTSP streams.
• Experience with video pipeline development: GStreamer, V4L2 (DeepStream is a plus).
• Basic experience connecting companion computers to flight controllers over UART/CAN/Ethernet.
• Understanding of video downlink constraints: digital vs. analog video, latency budgeting, bandwidth limits.
• Familiarity with hardware bring-up and peripheral integration (device trees or kernel modules are a plus).
• Ability to work with moderate supervision and take ownership of well-defined integration tasks.
   

Will Be a Plus

• Experience with thermal/IR cameras or night-vision imaging.
• Stabilized gimbal integration.
• RC link protocols: ExpressLRS, CRSF, SBUS.
• IMU integration and sensor fusion basics.
• GPS-denied navigation, visual odometry, or optical flow exposure.
• ROS/ROS2 experience.
• Multi-sensor time synchronization (PPS, hardware triggers, PTP).
• BSP customization or kernel module development.
• Model deployment pipelines on edge devices (TensorRT, ONNX).
• QGroundControl/Mission Planner usage or customization.
• Mission-critical or safety-critical systems experience.
   

Responsibilities

• Integrate and configure cameras, gimbals, and optical sensors on UAV platforms.
• Build and maintain low-latency onboard video pipelines and video downlink channels.
• Integrate companion computers with flight controllers running ArduPilot/PX4/Betaflight via MAVLink/MSP under senior guidance.
• Implement telemetry, command, and video control channels between drone and ground station.
• Perform camera calibration and sensor alignment.
• Collaborate with the CV team to ensure clean, well-timed data delivery to detection, tracking, and navigation modules.
• Help expose sensor and flight data to higher-level targeting and autonomy subsystems.
• Participate in hardware selection and system architecture discussions.
• Support flight testing, debugging, and system maintenance.
• Contribute to ensuring robustness of deployed systems under field and EW conditions.
   

Ideal Candidate Profile

You are a solid embedded engineer comfortable working close to hardware, with hands-on experience connecting cameras and sensors, building video pipelines on edge platforms, and communicating with flight controllers over MAVLink or MSP. You can debug interfaces and timing issues, follow integration specs, and are ready to grow into full ownership of the drone integration layer with the support of senior engineers.