About Us
At Autonomous Healthcare, we are at the forefront of medical innovation, developing the next generation of devices that will revolutionize patient care. Our mission is to commercialize breakthrough medical technologies by leveraging cutting-edge AI and autonomous systems. We believe that the best solutions are built together, and we are looking for a key member to join our collaborative R&D team.
The Role
We are seeking a talented and collaborative Signal Processing Engineer to join our multi-disciplinary team. In this role, you will work closely with hardware/software engineers and medical experts to transform raw sensor data into life-saving physiological insights.
Your contributions will be integral to the team's success. You will help design and build the signal processing pipelines that extract critical information from video, depth, and radar data streams. This is a hands-on role where your expertise will directly influence the development of our core technologies.
Key Responsibilities:
• Collaborate with the team to analyze complex, multi-modal sensor data to identify and isolate physiological signatures.
• Design, develop, and implement robust signal processing pipelines and machine learning models in Python.
• Work in close partnership with hardware/software engineers to define requirements, develop solutions, and integrate them into our broader systems.
• Rigorously test and validate algorithm performance, ensuring accuracy and reliability.
• Actively participate in team design reviews, brainstorming sessions, and peer reviews to foster innovation and maintain high standards.
Core Qualifications
• Deep expertise in signal processing theory and practice, including filtering (FIR,IIR), spectral analysis (FFT), wavelet analysis, and feature extraction.
• Proficiency in Python and its scientific computing stack (e.g., NumPy, SciPy, Pandas, scikit-learn, Matplotlib) within an environment like Jupyter Notebooks.
• Experience with human pose estimation from video, including familiarity with common architectures and the practical application of deep learning frameworks (PyTorch, TensorFlow) for keypoint detection and tracking.
• Excellent communication skills and a proven ability to work effectively in a collaborative, fast-paced R&D environment.
• B.S. in Electrical Engineering with 3+ years of relevant experience, or an M.S. with equivalent project experience.
Preferred Qualifications (Nice-to-Haves)
• Strong foundational knowledge of radar systems, including FMCW/CW principles and range-Doppler processing.
• Proficiency in C++ for performance-critical applications or algorithm deployment.
• Prior project experience in biomedical engineering, physiology, or medical device development.
• Familiarity with database querying using SQL.