AIML Engineer

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

Job summary

Tekskills Inc. is seeking an experienced AI/ML Engineer in Bengaluru. The role focuses on designing and implementing advanced machine learning solutions for resource-constrained devices, including model training, optimization, and deployment on MCUs and edge processors.

You will work with embedded AI frameworks and toolchains, and collaborate on real-world product applications while ensuring performance and efficiency across platforms.

Qualifications

• Must have M.Tech in AI/ML with EC/CS background.
• Total experience 4+ years, with at least 3+ years in AI/ML domain.

Responsibilities

• Perform model training, inference, and evaluation of AI models (supervised and unsupervised).
• Know model optimization and compression methods.
• Work with Embedded-AI frameworks (TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP).
• Use IDEs like Keil MDK, IAR Embedded Workbench, VS Code, Eclipse; toolchains from ST, NXP, Renesas, TI, Infineon.
• Understand MCU/DSP architectures; ARM Cortex-M/A processors; embedded memory architectures.
• Experience with FreeRTOS and Zephyr is an added advantage.
• Port and deploy AI models on resource-constrained devices (MCUs, DSPs, edge).
• Profile and optimize latency, throughput, memory, power.
• Proficient in Python and C/C++.
• Debugging and code optimization; Git/GitHub/GitLab; build systems like CMake, Makefiles.

Skills

Deep Learning

Python

C/C++

Model Training

AI/ML Frameworks

TensorFlow

PyTorch

Computer Vision

Unsupervised Learning

Edge AI

Education

M.Tech in AI/ML with EC/CS

B.E./B.Tech in EC/CS

Tools

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST Toolchain

NXP Toolchain

Renesas Toolchain

TI Toolchain

Infineon Toolchain

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.