AIML Engineer

Tekskills; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Tekskills is hiring an AI/ML Engineer to design, develop, and implement advanced ML solutions for embedded systems. You will work on model training, deployment on resource-constrained devices, and optimization for latency and power efficiency.

The role requires a strong academic foundation in AI/ML, experience with embedded frameworks, and proficiency in Python and C/C++. Collaboration with cross-functional teams will be essential for product and research applications.

Qualifications

• M. Tech in AI/ML with EC or CS; 4+ years total with 3+ years in AI/ML.
• Experience in training, inference, and evaluation of AI models on embedded devices.
• Strong Python and C/C++ programming skills.

Responsibilities

• Perform model training, inference, and evaluation of AI models (supervised and unsupervised).
• Implement model optimization and compression techniques.
• Work with embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
• Utilize IDEs and toolchains from major vendors (Keil MDK, IAR, VS Code, Eclipse, ST, NXP, Renesas, TI, Infineon).
• Understand MCU/DSP architectures and ARM Cortex-M/A processors; memory architectures.
• Experience with FreeRTOS/Zephyr is a plus.
• Port and deploy AI models on MCUs, DSPs, and edge devices.
• Profile latency, throughput, memory footprint, and power consumption.
• Familiar with Git/GitHub/GitLab and build systems like CMake, Makefiles.
• Communicate effectively orally and in writing.

Skills

Python

C/C++

CNN

RNN

GNN

Transformers

Unsupervised learning

Semi-supervised

Vision

Edge AI

NLP

Education

M. Tech in AI/ML with EC or 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

Job Summary

We are hiring for AI/ML Engineer.

Work mode: 5 days of WFO. Experience range: 4+ years. JD Embedded-AI engineer must have most of the below mentioned skillsets. 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). Different model optimization and compression methods must be known. Embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP. Experience of using IDEs like: Keil MDK, IAR Embedded Workbench, VS Code, Eclipse, and toolchains from ST, NXP, Renesas, TI, Infineon etc. 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. 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. Strong proficiency in Python and C / C++ languages. Experience with software debugging and code optimization techniques. Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles. Strong verbal and written communication skills.

Role Overview

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.

Responsibilities

• Perform model training, inference, and evaluation of different AI models (both supervised and unsupervised).
• Know various model optimization and compression methods.
• Embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
• Experience using IDEs like Keil MDK, IAR Embedded Workbench, VS Code, Eclipse, and toolchains from ST, NXP, Renesas, TI, Infineon etc.
• Strong understanding of MCU and DSP architectures; ARM Cortex-M/A processors and embedded memory architectures.
• Experience with FreeRTOS and Zephyr (added advantage).
• 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.
• Strong proficiency in Python and C / C++ languages.
• Experience with software debugging and code optimization techniques.
• Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles.
• Strong verbal and written communication skills.

Qualifications

• 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.

Core Skillset (Must-Have

• Expertise in Deep Learning architectures: CNN, RNN, GNN, Transformers.
• Strong programming skills in Python.
• Experience with at least one major AI/ML framework (PyTorch / TensorFlow).
• Track record in Computer Vision, Time-Series Analysis, Video Analysis.
• Familiarity with Unsupervised & Semi-supervised learning techniques.

Preferred/Good to Have

• Image Processing, NLP, Edge/Embedded AI deployment.

Additional Notes

Design and develop cutting-edge AI/ML models for vision, time-series, and multimodal data. Research and prototype advanced algorithms using state-of-the-art methods in deep learning. Optimize models for performance and scalability across platforms. Collaborate with cross-functional teams on real-world product and research applications. Stay ahead of AI/ML trends, and apply them creatively to business challenges.