The Role
Lead product development across hardware and software teams, manage budgets and resources, ensure compliance, and mentor team members in a medical AI company.
Summary Generated by Built In
Cardiosense is a rapidly growing, venture-backed medical AI company that is redefining how we detect, monitor, and manage heart disease. We're developing novel wearable sensors and advanced machine learning algorithms that translate raw physiological signals into clinically actionable, digital biomarkers used to detect early signs of cardiac worsening, guide personalized therapy, and improve patient outcomes.
Our team brings together experts in data science, biosignal analysis, and medicine united by a common mission to identify and combat preventable cardiac disease. Cardiosense's solutions are built on over a decade of clinical research and we continue to collaborate with the world's leading academic institutions to introduce the next generation of cardiac monitoring and disease management.
ABOUT THE ROLE:
As Head of Software/ML, you will provide execution leadership across multi-disciplinary product development teams spanning hardware, software, and machine learning. The ideal candidate will have a strong hands-on technical background combined with exceptional leadership skills and direct experience managing development of a Software-as-a-Medical Device (SaMD) solution from conception through FDA clearance.
WHAT YOU'LL BE DOING:
- Lead design, architecture, and development of software platform roadmaps
- Hire, coach, and groom a strong engineering organization optimized for lean, iterative, product development cycles
- Collaborate with product teams to translate user workflows into technical specifications and design implementations
- Develop and manage development budgets, resources, and timelines to ensure successful project delivery
- Directly manage the internal engineering team for development of software infrastructure. Oversee mechanical and electrical teams related to the development of wearable biosensor device
- Manage design and deployment of ML infrastructure from data ingestion to model deployment, supporting AI development from early feasibility to production rollout
- Define and implement agile software best practices, release management, CI/CD, code review, unit testing, and testing automation
- Ensure compliance with all relevant data privacy and cybersecurity standards
- Mentor and train team members on design techniques, systems architecture, and coding standards
QUALIFICATIONS:
- Engineering management including hands-on operations experience within a full-stack medical device company including class II/III devices, mobile gateways, mobile/desktop apps, cloud infrastructure, and data science
- 10+ years SW development experience along with 5+ years of experience managing development teams through full product lifecycle: from concept, through commercialization, to production maintenance
- Strong experience with microservices/containerization (e.g. Docker, Kubernetes etc.), infrastructure automation tools (e.g. Terraform, CloudFormation, etc.), and public cloud service providers (e.g. GCP, Azure, AWS)
- Strong desire to lead and develop junior team members
PREFERRED:
- Experience working with IoT devices, health data, and digital signal processing
- Familiarity with model deep learning tools such as TensorFlow and PyTorch
- Working in regulated environments (e.g. FDA, ISO 270001, 13485, 62304, HIPAA, SOC2, etc.)
- Experience with HL7, Smart on FHIR and Mirth Interface Engine
Cardiosense is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, religion, disability status, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Top Skills
AWS
Azure
CloudFormation
Docker
GCP
Kubernetes
Machine Learning
Microservices
PyTorch
Software-As-A-Medical Device
TensorFlow
Terraform
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The Company
What We Do
Contact: [email protected]
Cardiosense is building a physiological waveform data platform that leverages novel multi-modal sensors and industry-leading AI to develop predictive biomarkers for pre-symptomatic disease detection and enable personalized therapy.
