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AI Systems and Solutions Engineer
Intel
posted 30min ago
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Flexible timing
Key skills for the job
Job Description
- Responsible for the overall design and development of integrated Artificial Intelligence (AI) solutions for deep learning and machine learning systems that integrate hardware, software, firmware, board, and silicon components with specific focus on customer requirements and implementation limitations throughout the systems lifecycle.
- May also be responsible for AI systems architecture and definition, including translating the business opportunity into use cases and developing product specifications for required hardware and software needed to deliver system requirements.
- Impacts and influences the AI product roadmap and development based on profound comprehension of AI and deep learning algorithms, deep learning customer requirements, and deep learning software frameworks.
- Impacts related technologies/components such as memory, security, and OS that may be central to the final solution.
- Develops new methods in the areas of reinforcement learning, policy learning, computer vision, machine learning, simulation, sim2real, autonomous driving, and robotics.
- Leads design, analysis, and implementation of component level choices across the integrated AI systems on performance, features, and cost, including analysis of risks and emphasis on ease of use, reliability, security, availability, maintainability, sustainability, and quality.
- Defines systems implementation and integration approach and plans to ensure optimum performance and reliability across hardware and software that comprise the system.
- Delivers end to end technical solutions to solve customer problems, deploying solutions, executing benchmark tests, and preparing documentation.
- Conducts analysis and makes reliable engineering recommendations to ensure reliability/resiliency of the AI infrastructure.
- Monitors and reports on utilization and plans continuous process improvement.
- Collaborates with other teams to analyse next generation requirements and opportunities and may influence and guide research and academic collaboration in the space of cloud systems and solutions, including proof of concept and solutions beyond current industry approaches.
- Simulates real life environments in the cluster environment and analyses performance of prototypes. Contributes applied/customer knowledge to AI roadmap working with AI system architects.
Qualifications
- BTech /MTech in Computer Engineering, Computer Science, Information Systems, Electrical Engineering, or related field with 7+ years of relative experience.
- Strong understanding of GPU architecture and debug Skills.
- Validation exposure to GPU Pipeline, Preemption, power FW, limits management, current limit, GPU freq throttling, Secure fuse & interrupts
- Expertise in Linux Kernel debugging.
- Expertise in debugging PCIe specific Bugs Linux system /User mode programming (Expert).
- Good Knowledge on domains like PCIe, Memory, PM, FW, Boot loader(expert in minimum 2 domains).
- Knowledge on Shell, Python, C, C++Strong Self -learning and excellent communication capability.
- Experience with machine learning frameworks (PyTorch and/or Tensorflow) and their use in data science (Good to have). Knowledge in deploying and validating, AI, machine learning models (Good to have).
- Knowledge in intel/arm platform architecture and debug tools/frameworks(Good to have).
Employment Type: Full Time, Permanent
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Solution Engineer salary at Intel
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employee
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years exp.
₹14.4
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Flexible timing
Monday to Friday
No travel
Day Shift
Intel Benefits
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