Openings For Embedded AIML

Tekskills Inc.; Chennai; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Tekskills Inc. in Bangalore seeks an experienced Senior Software Engineer specialized in Embedded AI/ML. The role focuses on designing, developing, and deploying advanced machine learning solutions for resource-constrained devices.

You will work on state-of-the-art architectures, model optimization, and real-world problem solving, with 4+ years of total experience and at least 3+ years in AI/ML. M.Tech in AI/ML preferred; EC/CS background welcome.

Qualifications

• Strong AI/ML concepts with model training and evaluation.
• Experience with model optimization and compression methods.
• Experience deploying AI on MCUs, DSPs, edge devices.
• Proficient in Python and C/C++.
• Familiar with Git and build systems like CMake.

Responsibilities

• Design and develop advanced ML solutions for embedded systems.
• Optimize models for limited resources and power.
• Port and deploy AI models on MCUs and edge processors.

Skills

AI/ML concepts

Model training

Model optimization

Embedded AI frameworks

IDE proficiency

MCU/DSP architectures

RTOS knowledge

Porting AI models

Python

C/C++

Git tooling

Build systems

Communication skills

Education

M.Tech in AI/ML (EC/CS)

Tools

TensorFlow

TFLite

TFLM

microTVM

CMSIS-NN

CMSIS-DSP

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST toolchains

NXP toolchains

Renesas toolchains

TI toolchains

Infineon toolchains

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.