Embedded AIML Engineer

Experience : 4+ years

Location : Bangalore

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.

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.

Roles & Responsibilities :

- 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.

- 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.