Sr Firmware Engineer; Client: iRhythm Technologies

Sr Firmware Engineer (Client: iRhythm Technologies)

Location:

San Francisco, CA (5 days in a week onsite)

Duration: 9 months

IRC: IRC
294483

We are seeking a detail-oriented and collaborative firmware engineer to support development of cybersecurity updates to an IoT medical device that detects cardiac arrhythmias. This role is ideal for an experienced engineer who can quickly contribute to firmware design, implementation, debugging, and cross-functional development efforts in a regulated environment. The engineer in this role will work on resource-constrained embedded systems and contribute across the firmware lifecycle, including development, integration, debugging, investigation, documentation, and support for verification and release activities.

• Update existing firmware running on a resource-constrained embedded system to include cybersecurity enhancements such as encryption, updating SOUP components to current versions, and logging cyber events.
• Contribute to firmware design, implementation, integration, debugging, and release support.
• Participate in code reviews and follow established development practices and coding standards.
• Investigate and help resolve complex technical issues across firmware, hardware, wireless, power, manufacturing, and system interactions.
• Contribute to firmware documentation and development artifacts in support of regulated product development processes.
• Write and execute unit and integration testing.
• Resolve static code analysis warning and errors.
• Work hands‑on with company‑provided hardware for development and debugging, using appropriate lab setup (power supply, static mat, etc.).

• Proficiency in C with ability to adapt to company coding style; good commenting habits.
• Familiarity with software development lifecycle in a regulated environment (FDA preferred).
• Excellent proactive communication skills, both verbal and written, including through collaboration tools (e.g., Jira, Confluence, Teams).
• Bachelor’s degree in Computer Science, Computer Engineering or a related field.
• Experience interacting with software debugging in an embedded environment (IAR Embedded Workbench for Arm).
• Familiarity with version control systems (Git), and release methodologies.
• Familiarity with MISRA or other coding standards is a plus.
• Disciplined and detail-oriented; consistently delivers robust, readable code.
• Excellent analytical, problem solving skills and ownership of deliverables.

Rate:
As per market standards.

Client:
Global Logic Inc – Mitsubishi Electric

Position Type:
Contract

Location:

Detroit, MI (Fully onsite)

• Design and implement computer vision algorithms for object detection and segmentation using camera and LiDAR data fusion.
• Develop deep learning models for 2D and 3D object detection, including implementation and optimization of YOLO, Faster R‑CNN, SSD, and transformer-based architectures.
• Create and optimize LiDAR point cloud processing pipelines using PCL and Open3D for 3D object detection and segmentation.
• Implement sensor fusion techniques to combine camera and LiDAR data for enhanced object detection accuracy.
• Develop instance and semantic segmentation algorithms using state-of-the-art models like Mask R‑CNN, U‑Net, and Deep Lab.
• Implement and optimize deep learning models specifically designed for LiDAR point clouds, including Point Net, Point Net++, and other 3D neural network architectures.
• Develop robust perception algorithms that maintain performance in adverse weather conditions such as rain, snow, fog, and low-light scenarios.
• Build and maintain computer vision pipelines using OpenCV for image preprocessing, feature extraction, and geometric transformations.
• Design and implement multi‑object tracking systems using Kalman filtering, SORT, and DeepSORT algorithms.
• Work with ROS2 for integration and deployment of perception algorithms.
• Optimize deep learning models for edge deployment and real‑time inference performance.
• Develop robust evaluation metrics and testing frameworks for object detection systems.
• Collaborate with…