Embedded Machine Learning Engineer - Electronics and Software

Overall purpose:

Experienced embedded firmware/systems engineer with specific knowledge of machine learning and machine vision to join the Electronics and Software group.

• Work directly with customers and clients in multidisciplinary teams to understand their requirements, define tasks and take products from initial concept through to delivery.
• Produce client-focused communications, presenting and explaining technical work to a mix of technical and non-technical audiences.
• Define software system architecture, functional requirements, features and use cases.
• Use Python, C and C++ with machine learning frameworks to create intelligent embedded systems employing wired and wireless communications, sensors, user interfaces, and control for a range of applications.
• Develop high-quality code for production systems using modern software development tools and processes with software quality built in from the outset.
• Enhance 42 Technology’s software development offering through use of new development tools.

You will work with the wider 42 Technology team, and will report to Head of Embedded Systems.

Degree qualified in a relevant discipline such as electronic engineering or computer science.

Higher degree such as MEng, PhD.

• Demonstrable experience working with customers and clients to manage projects from procurement to delivery, with excellent verbal and written communication skills and the ability to present technical subjects persuasively to both technical and non-technical audiences.
• Demonstrable experience of firmware development for embedded products involving machine learning and/or machine vision, including an understanding of the processes and tools needed to develop maintainable high-quality embedded firmware.
• Experience working with the following:
  • Machine learning/vision platforms and frameworks such as Tensor Flow, Tensor Flow Lite, OpenCV and PyTorch.
  • A range of microcontroller/microprocessor types including Arm-based devices.
• Experience with test-driven development processes, such as unit testing, continuous integration, and regression testing, with an understanding of the appropriate use of third-party software.
• Excellent interpersonal skills with the ability to engage with colleagues and clients at all levels, a flexible, proactive and innovative approach to work and good attention to detail with an imaginative approach to problem solving.
• The ability to work independently with minimal supervision.

• Experience using NVIDIA Jetson or similar AI computing platforms.
• Wireless communications such as Bluetooth, WLAN, cellular, low-power radio.
• Wired communications such as CAN, RS232, RS485, SPI and I2C.
• Real-time signal conditioning and filtering.
• Low-power or battery-powered systems.
• Experience of medical device development and the IEC 62304 software life cycle for medical products.
• Knowledge of encryption and security for embedded systems.
• Broad knowledge of electronic systems for control, communications, sensing, and user interaction.
• Development of systems on embedded Linux platforms.