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.
- Robust 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.
- Solid 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.

📌 AIML Engineer (Bengaluru)
🏢 Tekskills
📍 Bengaluru