Embedded AI/ML Engineer
First seen by Alion on Sep 22, 2026.
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.
Skills
Artificial Intelligence, Machine Learning, Deep Learning, R-CNN, Python, Tensorflow, Computer Vision, Time Series Analysis, FreeRTOS