Lead Edge AI Engineer

Work in a team of self-motivated engineers and equally contribute for success of the project

Take ownership of assigned responsibilities, flexible with work timings, attend and contribute to technical discussions.

Read and understand hardware block diagram & schematics/data sheets/software design notes

Design and Develop Edge AI applications for the Embedded System

Identify the right AI models for specific use cases, Port and optimize AI models for real-time performance

on resource-constrained embedded systems

Comply with Performance and Quality standards for the project

Conduct self-review and peer review of work in the project

Interact with internal and external stake holders

Use optimum design patterns for AI usage

Proficiency in C/C++ and python programming

Hands-on experience in deploying AI models on embedded platforms.

Experience working with MCU, bare-metal, RTOS and Edge AI/ML applications

Experience working with multi-core, multi-threaded applications, IPC and task scheduling

Strong knowledge in board bring-up and interfaces such as OSPI, GPIO, UART, SRAM, SDRAM etc.

Good debugging and problem-solving skills.

Experience in various profiling tools, and proficiency in identifying deviations from expected behaviour and finding their root causes

Ability to use Hardware test equipment: Joulescope, oscilloscope, logic analyzer and JTAG

Understanding of system constraints like memory, compute, and power on edge devices.

Good communication skills for clearly communicating ideas and concepts to team/customer