R&D center WINSTARS.AI

This project aims to enable GPS-independent navigation, last-mile autonomy, and coordinated multi-agent behavior in complex environments through onboard AI.

Responsibilities:
• Design and integrate real-time SLAM pipelines (visual-inertial preferred) for autonomous navigation.
• Object tracking algorithms using OpenCV.
• Train and deploy lightweight ML models for onboard inference in real-world conditions.
• Integrate AI/ML modules for target detection and behavioral decision-making.
• Support GPS-agnostic navigation via sensor fusion and terrain-aware motion planning.
• Collaborate with embedded, full-stack, and hardware teams to align the autonomy stack with system-
level constraints.
• Optimize performance on ARM-based edge compute platforms (Raspberry Pi, Jetson Nano, etc.).

Requirements:
• Minimum 7 years of experience in autonomy, robotics, or computer vision systems.
• Proficient in OpenCV, visual SLAM, and real-time localization.
• Strong skills in C++ and Python; experience with ROS/ROS2.
• Demonstrated experience with ML model training and deployment (TensorFlow, PyTorch, etc.).
• Ability to run perception and AI systems on embedded Linux hardware.
• Understanding of flight dynamics and real-time motion planning.
• Ability to debug and tune systems in field environments.
 

Preferred Qualifications:
• Experience with ArduPilot, PX4, or similar UAV control frameworks.
• Familiarity with object detection models (e.g., YOLO, MobileNet) and model quantization.
• Experience with multi-agent autonomy, swarm logic, or distributed path planning.
• Background in defense, tactical robotics, or mission-critical systems.
• English level not lower than B2
• Agile development experience (Jira, Git).

The role directly supports core product capabilities, including GPS-agnostic SLAM navigation.

In this role, you will contribute to high-performance embedded systems that power autonomous, including EW—enabled capabilities for signal detection, interference resilience, and secure communication.

Responsibilities:

• Design, develop, and optimize embedded software for Raspberry Pi and STM32 systems.
• Implement robust UART, I2C, SPI, and IMU integration for hardware—software interfacing.
• Manage power logic, boot processes, watchdogs, and runtime reliability.
• Integrate RF modules, SDR interfaces, and low-level signal-processing routines for EW and telemetry systems.
• Collaborate with autonomy, AI, DevOps, and hardware teams across locations.
• Support integration with ArduPilot, ROS, and swarm-control frameworks.
• Participate in testing and validation of RF performance, signal jamming resistance, and EMI mitigation.

Requirements:

• Minimum 5 years of experience in embedded systems development.
• Strong proficiency in C/C++ and Python on Linux (Debian-based preferred).
• Proven experience with FPV or robotics hardware and GPIO-level programming.
• In-depth knowledge of UART, I2C, IMU sensors, and system-level debugging.
• Experience with RF communication systems or signal-processing frameworks (DSP/SDR).
• Ability to work independently in a remote or hybrid engineering environment.

Preferred Qualifications:

• Direct experience working with UAV platforms, or robotic systems.
• Familiarity with ArduPilot, PX4, or similar autopilot software.
• Prior work on tactical, edge, or defense-related hardware projects, especially in Electronic Warfare (EW), SIGINT, or ECM/ECCM.
• Understanding of Software-Defined Radio (SDR) tools (e.g., USRP, HackRF, BladeRF).
• Experience with RF front-end design, spectrum analysis, or anti-jamming techniques.
• Agile project management via Jira, version control via GitHub.
• English level: B2