Senior Systems Engineer
4 weeks ago
Minimum Qualifications:
- 5+ years of experience developing complex products involving hardware and a significant level of embedded software.
- Possess an in-depth knowledge of intricate hardware design and troubleshooting.
- Strong background in machine learning algorithm development, systems integration, and hardware-software interfacing.
- Advanced degree in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field. A Ph.D. is a plus but not required.
- Strong analytical skills to troubleshoot issues and find efficient solutions
Preferred Qualifications:
- 10+ years' experience in DSP engineering or a related field.
- Hands-on experience with medical imaging technologies and understanding of their application in biomedical fields.
- Experience in integrating AI functionalities within hardware systems in a healthcare setting.
- Experience in managing a team and cross-functional collaboration.
ABOUT THE ROLE
Tiposi is a pioneering medical device startup at the forefront of innovation, specializing in low-frequency, low-power radar sensor technology. Our cutting-edge device leverages AI to analyze data captured via advanced sensors, providing critical insights into the body without relying on traditional imaging outputs. Currently in the clinical trial phase, we are dedicated to revolutionizing stroke detection and enhancing the quality of life, comfort, and safety for patients. Our mission is to create life-saving technology that is both innovative and accessible, streamlining medical experiences and ensuring complete privacy through non-intrusive, efficient solutions.
The Senior AI Systems Engineer will oversee our AI/ML team, guiding the integration and optimization of ML-driven analysis tools within our medical device framework. This senior role demands a deep understanding of both machine learning algorithms and hardware engineering principles, especially as they relate to sensor technology and digital signal processing. The ideal candidate will play a crucial role in ensuring system integrity and operational efficiency by diagnosing and resolving cross-disciplinary issues.
Responsibilities:
- Develop and refine algorithms that analyze sensor data to ensure actionable and reliable insights.
- Diagnose and troubleshoot issues across AI and hardware domains, identifying whether discrepancies or malfunctions arise from software algorithms or physical hardware components.
- Facilitate effective communication between the AI and hardware teams, bridging technical gaps and aligning project objectives with company goals.
- Collaborate with the hardware engineers to seamlessly integrate AI functionalities into the device architecture, focusing on system reliability and efficiency.
- Maintain up-to-date knowledge of industry standards and technological advancements in AI, machine learning, and medical device regulations to ensure compliance and competitive edge.
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