Openings For Embedded AIML Engineer

Tekskills Inc.; Karnataka; Vor Ort; INR 1.500.000 - 2.100.000; Vollzeit

Zusammenfassung

Tekskills Inc. is seeking an Embedded AI/ML Engineer in Bangalore with 4+ years of experience. You will work on AI/ML concepts, porting models to MCUs and edge devices, and optimizing performance across latency, memory footprint, and power usage.

You will utilize frameworks like TensorFlow, TFLite, and CMSIS-NN, and collaborate with teams across software and hardware domains. Proficiency in Python and C/C++, plus strong communication, is required.

Qualifikationen

• Strong understanding of AI/ML concepts.
• Model training, inference, and evaluation of AI models (supervised/unsupervised).
• Model optimization and compression methods knowledge.
• Embedded-AI frameworks: TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
• Experience with IDEs like Keil MDK, IAR, VS Code, Eclipse and toolchains from major vendors.

Aufgaben

• Port and deploy AI models on resource-constrained devices (MCUs, DSPs, edge).
• Profile and optimize latency, throughput, memory, and power consumption.
• Collaborate with hardware teams to integrate AI pipelines.
• Deliver robust embedded AI software with clean, documented code.

Kenntnisse

Mathematics & algorithms

TensorFlow

DSP

MCU

Tools

Keil MDK

IAR Embedded Workbench

VS Code

Eclipse

ST toolchains

NXP toolchains

Jobbeschreibung

Hi

We are hiring for Embedded AI/ML Engineer

Experience: 4+ Years

Location: Bangalore

Mandatory skills:

• Strong exp on mathematical and algorithm
• Strong exp on Tensor flow, DSP, MCU

JD:

1. Must be good at AI-ML concepts. Must be able to perform model tr
2. aining, inference, and evaluation of different AI models (both supervised and unsupervised).
3. Different model optimization and compression methods must be known.
4. Embedded-AI frameworks like TensorFlow, TFLite, TFLM, microTVM, CMSIS-NN, CMSIS-DSP.
5. Experience of using IDEs like: Keil MDK, IAR Embedded Workbench, VS Code, Eclipse, and toolchains from ST, NXP, Renesas, TI, Infineon etc.
6. 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.
7. 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.
8. Strong proficiency in Python and C / C++ languages. Experience with software debugging and code optimization techniques.
9. Familiarity with Git/GitHub/GitLab and build systems like CMake, Makefiles.
10. Strong verbal and written communication skills.