Openings For AIML

Tekskills Inc.; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tekskills Inc. in Bangalore seeks an Embedded AIML Engineer with 4+ years of hands-on experience to design and optimize AI solutions for resource constrained devices.

You will train, deploy, evaluate models, and optimize latency, memory footprint and power, porting AI workloads to MCUs, DSPs and edge processors.

Strong skills in Python and C/C++, plus experience with FreeRTOS/Zephyr and common IDEs and toolchains, are essential for success.

Qualifications

• 4+ years of embedded AI/ML experience.
• Experience deploying AI models to resource-constrained devices.
• Strong debugging and optimization skills in Python and C/C++.

Responsibilities

• Develop embedded AI solutions for MCU/DSP/edge devices.
• Port AI models to MCUs, optimize latency, memory and power.
• Collaborate with hardware/firmware teams to integrate AI workloads.

Skills

AI/ML concepts

Model training/inference/evaluation

Model optimization & compression

Embedded-AI frameworks

IDE experience

Toolchains awareness

MCU/DSP architectures

FreeRTOS/Zephyr

Python

C/C++

Git/GitHub/GitLab

CMake/Makefiles

Communication skills

Job description

Hi all

We are hiring for Embedded AIML Engineer

Work Location: Bangalore

Work mode: 5 days of WFO

Experience Range:4+ years

JD:

Embedded-AI engineer must have most of the below mentioned skillsets.

1. Must be good at AI-ML concepts. Must be able to perform model training, inference, and evaluation of different AI models (both supervised and unsupervised).
2. Different model optimization and compression methods must be known.
3. Embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
4. Experience of using IDEs like: Keil MDK, IAR Embedded Workbench, VS Code, Eclipse, and toolchains from ST, NXP, Renesas, TI, Infineon etc.
5. Strong understanding of MCU and DSP architectures. Knowledge of ARM Cortex-M/A processors and embedded memory architectures. Experience with: FreeRTOS and Zephyr is an added advantage.
6. Experience in porting and deploying AI models on resource-constrained devices such as MCUs, DSPs, and edge processors. Performance profiling and optimization of Latency, Throughput, Memory footprint, and Power consumption.
7. Strong proficiency in Python and C / C++ languages. Experience with software debugging and code optimization techniques.
8. Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles.
9. Strong verbal and written communication skills.