Rust Jobs for Rustaceans

Key Responsibilities:

• Design & Development:
  • Develop robust applications in Rust for real-time medical devices running on embedded Linux.
  • Implement and optimize algorithms for data processing in regulated healthcare environments.
  • Ensure seamless integration between software and hardware components as well as cloud backend services
• Collaboration:
  • Work closely with our science team to translate requirements into tailored software solutions.
  • Collaborate with systems and hardware engineers to integrate software with embedded systems.
• Compliance & Quality:
  • Ensure all software adheres to medical device regulations (e.g., FDA, ISO 13485).
  • Drive the adoption of best practices in software engineering, including automated testing, CI/CD pipelines, and robust version control strategies.
• Mentorship & Leadership:
  • Provide technical guidance to junior engineers.
  • Lead initiatives and drive continuous improvement within the team.
• Innovation:
  • Stay at the forefront of advancements in Rust programming, embedded systems, and medical device development.
  • Contribute to the validation, documentation, and testing processes to align with internal quality systems.

Requirements:

• Strong proficiency in Rust programming with experience developing production-grade applications.
• Expertise in embedded Linux systems and development tools.
• Familiarity with interfacing with firmware components and on board peripherals.
• Proven experience in regulated industries such as medical devices or biotechnology.
• Experience with cloud platforms like AWS or GCP for scalable data storage and analysis.
• Knowledge of workflow management tools and containerization technologies (e.g., Docker, Kubernetes).
• Strong problem-solving skills with a focus on building compliant and efficient solutions.

Preferred Skills:

• Familiarity with medical device standards like IEC 62304 or FDA regulations.
• Experience optimizing bioinformatics algorithms for real-time applications.
• Knowledge of cybersecurity best practices for protecting sensitive patient data.
• Background in machine learning or data analytics within healthcare settings.