Openings For Embedded AIML

Tekskills Inc.; Kolkata District; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Tekskills Inc. in Bangalore is seeking an experienced Embedded AIML Engineer. The role focuses on designing, developing, and deploying advanced ML solutions on resource-constrained devices.

The candidate should have 4+ years of total experience, with at least 3+ years in AI/ML, and a strong background in EC or CS. Proficiency in Python and C/C++, and hands-on with MCU architectures is essential.

Qualifications

• M. Tech in AI/ML with EC or CS background.
• 4+ years total experience, 3+ years in AI/ML domain.
• Strong AI/ML foundation and research background.

Responsibilities

• Design, develop, and implement ML/DL solutions.
• Work with state-of-the-art architectures and optimization.
• Port AI models to resource-constrained devices.
• Profiling latency, throughput, memory, and power.

Skills

AI/ML concepts

Model training

Inference

Model optimization

Embedded frameworks

MCU architectures

Python

C/C++

Git workflows

Debugging

ARM Cortex-M

Education

M.Tech in AI/ML

Tools

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST Toolchains

NXP

Renesas

TI

Infineon

Job description

Hi

We are Embedded AIML Engineer

Work Location: Bangalore

Work mode: 5 days of WFO

Experience Range:4+ years

Mandatory:

• M. Tech in AI/ML with background in Electronics & Communication (EC) or Computer Science (CS).
• Experience: 4+ years total, with at least 3+ years relevant in AI/ML domain.

JD:

Position: Senior Software Engineer
We are seeking an experienced AI/ML Engineer with a strong academic and research foundation to contribute to the design, development, and implementation of advanced machine learning and deep learning solutions. The role requires expertise in state-of-the-art architectures, model optimization, and problem-solving applied to real-world scenarios.

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.