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Urgent! Embedded AI Engineer Job Opening In tamil nadu – Now Hiring Valeo
Responsibilities :
Deep Learning Model Conversion: Convert and adapt deep learning network architectures (e.g., from PyTorch) for deployment on various embedded platforms.
Quantization-Aware Training (QAT): Implement and fine-tune Quantization-Aware Training techniques to optimize model performance and reduce memory footprint while maintaining accuracy.
Model Optimization: Perform extensive model optimization techniques, including pruning, quantization (post-training and QAT), and network architecture search, to achieve desired latency, power, and memory targets.
Runtime Integration: Integrate optimized deep learning models with embedded runtime environments and hardware accelerators.
Performance Profiling & Tuning: Analyze and profile model performance on target embedded hardware, identifying bottlenecks and implementing solutions for real-time inference.
Number Format Conversion: Work with various number formats (e.g., FP32, FP16, INT8) and develop strategies for efficient conversion and utilization on embedded processors.
Toolchain Development & Utilization: Utilize and contribute to the development of custom conversion tools and optimization scripts to streamline the deployment pipeline.
Skills Required :
Experience: 5+ years of experience in embedded software development with a strong focus on AI/Machine Learning deployment.
Programming Skills: Proficient in Python for AI development and scripting.
Deep Learning Frameworks: Hands-on experience with deep learning frameworks such as PyTorch.
Experience with TensorFlow/Keras is a plus.
Embedded Systems: Strong understanding of embedded system architectures, microcontrollers, DSPs, and/or FPGAs.
Optimization Techniques: Proven experience with deep learning model optimization techniques (quantization, pruning, knowledge distillation).
Number Formats: Familiarity with different number formats (e.g., FP32, FP16, INT8) and their implications for embedded inference.
Conversion Tools: Experience with model conversion tools (e.g., ONNX, OpenVINO, TensorRT, TVM).
Problem-Solving: Excellent analytical and problem-solving skills, with a strong ability to debug and optimize complex systems.
Experience with C/C++ for embedded development.
Familiarity with hardware acceleration (e.g., NPUs, GPUs on edge devices).
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Unlock Your Embedded AI Potential: Insight & Career Growth Guide
Real-time Embedded AI Jobs Trends in tamil nadu, India (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Embedded AI in tamil nadu, India using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 114554 jobs in India and 31 jobs in tamil nadu. This comprehensive analysis highlights market share and opportunities for professionals in Embedded AI roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Valeo is currently hiring and seeking a Embedded AI Engineer to join their team. Feel free to download the job details.
Wait no longer! Are you also interested in exploring similar jobs? Search now: Embedded AI Engineer Jobs tamil nadu.
An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Valeo adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Embedded AI Engineer Jobs India varies, but the pay scale is rated "Standard" in tamil nadu. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Embedded AI Engineer typically include Other General and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your Embedded AI Engineer interview at Valeo, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Valeo's products or services and be prepared to discuss how you can contribute to their success.
By following these tips, you can increase your chances of making a positive impression and landing the job!
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