Overview

Openings For Embedded AIML Engineer (Kolkata)

Responsibilities

• 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

Qualifications

• We are hiring for Embedded AIML Engineer
• Location: Bangalore
• We are seeking an experienced AI/ML Engineer with a robust 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.
• M.Tech in AI/ML with background in Electronics & Communication (EC) or Computer Science (CS).
• Core Skillset (Must-Have):
• Expertise in Deep Learning architectures: CNN, RNN, GNN, Transformers.
• Strong programming skills in Python.
• 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