Software Engineer, Athelas Home
Commure · Remote · Sao Paulo, Brazil ·
COMPENSATION
$40k – $50k
Listed on the employer's job board (Ashby)
- Fully remote
- Python + React
- IoT Medical Device
- Kubernetes + Docker
- FDA-cleared Product
Join the Athelas Home Engineering team at Commure to enhance a portable IoT device that performs hematology analysis from a few drops of blood. You will work in a small, multi-functional group alongside chemical, hardware, and quality engineers to improve infrastructure and build new features.
The position requires translating product requirements into technical solutions while maintaining high standards for code quality, security, and system reliability. Your work directly impacts patient care by making bloodwork more accessible and comfortable.
What you'll do
- Develop and improve backend and frontend services for the Athelas device
- Architect robust and scalable back-end infrastructure
- Translate product requirements into effective technical solutions
- Implement cybersecurity best practices throughout the development lifecycle
- Collaborate with operations, quality, and regulatory teams for compliance
- Diagnose and resolve technical issues to ensure system stability
- Establish best practices for code quality, testing, and deployment
What you'll need
- Bachelor’s or Master’s in Computer Science or equivalent experience
- Professional software engineering experience with proficiency in Python
- Deep expertise in developing and managing data pipelines
- Experience with PostgreSQL or similar relational database systems
- Advanced knowledge of Containerization and Cloud Services like Docker and Kubernetes
- Proven ability to build, scale, and maintain sophisticated production environments
- Strong skills in system monitoring, alerting, and software reliability engineering
Nice to have
- Interest in embedded software engineering for Linux-based IoT devices
- Experience with hardware interfaces such as GPIO, camera control, or serial communication
- Background in designing or optimizing computer vision models for diagnostics
- Familiarity with the ML lifecycle from data preparation to model deployment
Stack
- Python
- Flask
- React
- Postgres
- Kubernetes
- Docker