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At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
Join us to push the boundaries of scaling AI. The AI Infra team is responsible for scaling LinkedIn’s AI model training, feature engineering and serving with hundreds of billions of parameters models for all AI use cases from recommendation models, large language models, to computer vision models. We optimize performance across algorithms, AI frameworks, data infra, compute software, and hardware. In this role, you will be responsible for implementing and deploying AI models on the Field Programmable Field Array (FPGA) hardware. You will integrate FPGAs in our current CPU and GPU fleet, and develop high-performance and power-efficient FPGA solutions for the large scale AI models.
As a Sr. Staff Engineer on the AI Infra team, you will play a crucial role in building the next-gen AI inference infrastructure. You will design and implement FPGA kernels in High Level Specification (HLS) or Hardware Description Language (Verilog, VHDL) and the host code to connect with the kernels. You will be responsible for the kernel development lifecycle (including but not limited to synthesis, place-and-route, timing analysis, validation and verification) and deploy them on hardware platforms (such as AMD Alveo) in LinkedIn data centers. You will develop toolchains to generate FPGA kernels from high-level AI frameworks such as PyTorch, Tensorflow, JAX. You will also develop tooling for monitoring and observability of AI models running on FPGA. This role gives you the unique opportunity to work with a wide spectrum of AI practitioners, AI Infra, Compute Infra, and Data Center Infra teams.
Responsibilities
Deliver impact by driving innovation while building and shipping software at scale
Design, implement, and optimize the performance of large-scale AI models on FPGA for personalized recommendation, large language models, and video models.
Improve the observability and understandability of the FPGA fleet with a focus on improving developer productivity and system sustenance.
Provide architectural guidance on modern FPGA platforms, tools, and workflows to up-level the engineering organization
Mentor other engineers, define our challenging technical culture, and help to build a fast-growing team.
Function as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI Platforms.
Basic Qualifications:
BS/BA in Computer Science or related technical field or equivalent technical experience
5+ years of industry experience in hardware design, software design, and algorithm related solutions
5+ years of experience programming in HLS or HDL languages such as C++, SystemC, Verilog, VHDL; and software languages such as Python
5+ years of experience with FPGA development software such as AMD Vitis and Vivado, Intel Quartus.
2+ years of experience as an architect, or technical leadership position
Hands-on experience developing FPGA hardware solutions and deployment at scale.
Familiarity with deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX
Preferred Qualifications:
BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience
2+ years of experience in hardware acceleration of AI/ML models
Experience in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX
Familiarity with building ML applications, LLM serving, GPU serving.
Familiarity with containers and container orchestration systems
Outstanding interpersonal communication skills (including listening, speaking, and writing) and ability to work well in a diverse, team-focused environment with other SRE/SWE Engineers, Project Managers, etc.
Suggested Skills:
FPGA development
AI/ML hardware acceleration
Systems Infrastructure
LinkedIn is committed to fair and equitable compensation practices.
The pay range for this role is $180,000 to $300,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.
Equal Opportunity Statement
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