Openings For AIML Engineer_Bangalore

Tekskills Inc.; Karnataka; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Tekskills Inc. in Bangalore seeks an Embedded AIML Engineer to contribute to design, development, and deployment of AI/ML solutions for embedded devices.

The role requires 4+ years total experience with at least 3+ years in AI/ML, and hands-on expertise with embedded AI frameworks and MCU/DSP architectures. This is a 5-day WFO position with a strong emphasis on practical model optimization.

Qualifications

• M. Tech in AI/ML with EC or CS background.
• Total 4+ years experience; at least 3+ years in AI/ML.

Responsibilities

• Contribute to design, development, and implementation of advanced ML solutions.
• Perform model training, inference, and evaluation for supervised and unsupervised models.
• Apply model optimization and compression techniques.
• Work with embedded AI frameworks and MCU/DSP architectures.

Skills

AI/ML concepts

Model training

Inference

Model evaluation

Model optimization

Compression methods

Embedded-AI frameworks

IDEs & toolchains

MCU & DSP

FreeRTOS/Zephyr

DL architectures

Python programming

Education

M.Tech in AI/ML with EC/CS background

Tools

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST toolchains

NXP toolchains

Renesas toolchains

TI toolchains

Infineon toolchains

Job description

Hi

We are looking for 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.

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.

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. Expertise in Deep Learning architectures: CNN, RNN, GNN, Transformers.
7. Strong programming skills in Python.