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Embedded Software Engineer

3 months ago


Singapore Cygnify Pte Ltd Full time

Responsibilities:

Embedded Software Development:

Design, develop, and maintain embedded software for AI banking solutions.
Write efficient, reliable, and scalable code for embedded systems.
Ensure high performance, reliability, and security of embedded applications.

Integration and Testing:

Integrate embedded software with hardware components and other system modules.
Develop and execute unit and integration tests to ensure software quality.
Troubleshoot and resolve issues in development, test, and production environments.

AI and Machine Learning:

Collaborate with AI and machine learning teams to integrate AI algorithms into embedded systems.
Optimize AI models and algorithms for real-time embedded processing.

System Architecture:

Contribute to the design and architecture of embedded systems, ensuring they meet performance and scalability requirements.
Participate in code and design reviews to maintain high standards of software quality.

Collaboration and Documentation:

Work closely with cross-functional teams, including hardware engineers, AI researchers, and product managers, to deliver comprehensive solutions.
Document software design, implementation, and testing processes clearly and accurately.

Continuous Improvement:

Stay updated with the latest developments in embedded systems, AI, and related technologies.
Identify areas for improvement and implement best practices to enhance system performance and reliability.

Requirements:

Education and Experience:

Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, or a related field.
3+ years of experience in embedded software development, preferably within the financial technology or AI industry.

Technical Skills:

Proficiency in programming language such as C.
Strong knowledge of embedded systems architecture and real-time operating systems (RTOS).
Experience with microcontrollers, ARM processors, and other embedded hardware platforms.
Familiarity with AI and machine learning frameworks and tools.
Experience with communication protocols (e.g., I2C, SPI, UART) and interfacing with hardware components.
Proficiency in using debugging tools and techniques for embedded systems.

Soft Skills:

Strong problem-solving and analytical skills.
Excellent communication and teamwork abilities.
Ability to work independently and manage multiple tasks effectively.

Preferred Qualifications:

Experience with AI and machine learning integration in embedded systems.
Knowledge of security practices and standards for embedded systems.
Familiarity with version control systems (e.g., Git) and CI/CD pipelines.

Benefits:

Competitive salary and performance-based bonuses.
Comprehensive health insurance and wellness programs.
Opportunities for professional development and career growth.
A collaborative and innovative work environment.