Provides technical expertise to Intel sales teams, external partners, and end-customers.
Acts as a key advisor and thought leader to the technical sales teams, while driving vision, value, and strategy around technical solutions.
Understands the business use case and technical merits of a solution, co-owns relationships with customer/partner decision-makers to solve complex challenges across system(s) and influences the customers purchasing decision for specific accounts.
Supports Intel sales professionals, including those in technical sales roles, in design and deal win engagements by delivering Intel platform and portfolio value propositions and providing ongoing technical support on product briefings.
Understands competitive landscape to deliver use-case based benchmarks and drive customer driven technical incubations.
Supports customer design win needs and facilitates product and program updates.
Liaises with BUs to relay roadmap, product, program and technical updates to field sales and external partner teams.
Plans and implements training roadmap, assets, schedule, availability, and delivery.
Articulates the voice of customer back to product development teams to help define platform enabling, roadmap, program, samples, and other enabling requirements.
Key Responsibilities:
Act as the go-to person for all AI, ML and Data Analytics workloads.
Build repeatable technical assets such as workshops, scripts, reference architectures to facilitate adoption of Intel GenAI portfolio.
Develop and optimize AI models on Xeon processors to enhance performance and efficiency.
Deeply understand and utilize Intel CPU architecture and Intel Software Optimizations such as IPEX, Openvino, etc. to maximize computational power for AI applications.
Implement and fine-tune AI models, ensuring high accuracy and performance in inferencing tasks.
Work with state-of-the-art AI frameworks and tools, including Hugging Face, vLLM, Langchain, and quantization techniques.
Collaborate with cross-functional teams to deploy AI solutions on cloud platforms such as AWS and GCP.
Stay updated with the latest advancements in AI and cloud technologies to continuously improve our AI infrastructure.
Closely working with customer engineering team and lead successful POC completion.
Proven experience in developing and deploying AI models.
Hands-on experience with AI model benchmarking, inferencing and fine-tuning.
Proficiency with AI frameworks, tool and libraries, including PyTorch, Hugging Face, vLLM, RAG, Langchain, and quantization methods.
Solid knowledge of cloud platforms, particularly AWS/GCP/Azure-Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center compute/network/storage deployments.
Excellent problem-solving skills and the ability to work in a fast-paced environment.
Strong communication skills and the ability to collaborate effectively with team members.
Experience delivering/leading workshops, training sessions, and presenting technical solutions to diverse audiences.
Preferred Skills:
In-depth knowledge of Artificial Intelligence concepts including server/storage architecture, batch/stream processing, data warehousing, data lakes, distributed filesystems, OLTP/OLAP databases and data pipelining tools.
Experience with AI accelerators such as GPU or ASICs.
Familiarity with additional cloud platforms and services.
Contributions to open-source AI projects.
Understanding of Intel CPU architecture and its application.
Understanding of Intel AI software optimizations.
*Job posting details (such as work model, location or time type) are subject to change.
McGraw Hill
Skylight
NVIDIA
KODIF
Oowlish
