Openings For AIML

Tekskills Inc.; Delhi; Presencial; INR 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Tekskills Inc. is hiring an Embedded AIML Engineer for a Bangalore-based, five-days-a-week WFO role. The candidate should have 4+ years of hands-on experience in AI/ML, embedded AI frameworks, MCU/DSP architectures, and proficiency in Python and C/C++.

Prior work with RTOS like FreeRTOS/Zephyr is advantageous and strong communication skills are required. The role involves porting AI models to resource-constrained devices such as MCUs/dsped edge hardware, optimizing latency, throughput and memory

Formación

• Candidates must have strong AI/ML knowledge and be able to train, infer, and evaluate models.
• Experience with model optimization and compression methods.
• Experience with embedded AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
• Proficiency with IDEs such as Keil MDK, IAR Embedded Workbench, VS Code, Eclipse and toolchains from ST, NXP, Renesas, TI, Infineon.
• Strong understanding of MCU and DSP architectures; knowledge of ARM Cortex-M/A processors and embedded memory; experience with FreeRTOS and Zephyr is a plus.
• Experience porting and deploying AI models on resource-constrained devices (MCUs, DSPs, edge) with performance profiling.
• Strong Python and C/C++ coding skills; debugging and optimization.
• Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles.
• Excellent written and verbal communication skills.

Conocimientos

AI/ML concepts

Model training

Model inference

Model optimization

Embedded AI frameworks

MCU/DSP architectures

ARM Cortex-M/A

FreeRTOS/Zephyr

Python

C/C++

Git/GitHub/GitLab

Code debugging

Communication

Herramientas

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST toolchains

NXP toolchains

TI Toolchains

Infineon toolchains

Descripción del empleo

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.