Openings For Embedded AIML Engineer

Tekskills Inc.; Dadri; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Tekskills Inc. in Bangalore seeks an experienced Embedded AIML Engineer to design, develop and optimize AI/ML solutions for edge devices. Candidates should have 4+ years of total experience with strong foundations in AI/ML, computer vision, time-series, and multimodal data.

You will work with Python and C/C++, port models to MCUs and DSPs, and collaborate with cross-functional teams to deliver scalable embedded AI applications.

Qualifications

• M.Tech in AI/ML with EC or CS; 4+ years total, 3+ years in AI/ML domain.
• Deep Learning architectures: CNN, RNN, GNN, Transformers; Python proficiency.
• Experience with PyTorch or TensorFlow; Computer Vision/Time-Series/Video analysis; unsupervised & semi-supervised learning.
• Nice to have: Image processing, NLP, Edge/Embedded AI deployment.

Responsibilities

• Design and develop AI/ML models for vision, time-series, and multimodal data.
• Research and prototype advanced algorithms with state-of-the-art methods.
• 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 to business challenges.

Skills

Deep Learning architectures (CNN, RNN,

Transformers

Python

C/C++

Model training/inference/evaluation

Python & ML frameworks (PyTorch, TF)

Visualization & CV tasks

Education

M.Tech in AI/ML (EC/CS)

Tools

PyTorch

TensorFlow

TensorFlow Lite (TFLite)

TFLM

microTVM

CMSIS-NN

CMSIS-DSP

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

CMake

Makefiles

Git/GitHub/GitLab

ST/NXP/Renesas/TI/Infineon toolchains

Job description

Hi

We are hiring for 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 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.

1. 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).
2. Different model optimization and compression methods must be known.
3. Embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
4. Experience of using IDEs like: Keil MDK, IAR Embedded Workbench, VS Code, Eclipse, and toolchains from ST, NXP, Renesas, TI, Infineon etc.
5. 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.
6. 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.
7. Strong proficiency in Python and C / C++ languages. Experience with software debugging and code optimization techniques.
8. Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles.

Strong verbal and written communication skills