
Founded in 2003, LinkedIn connects the world's professionals to make them more productive and successful. With more than 1 billion members worldwide, including executives from every Fortune 500 company, LinkedIn is the world's largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions and Premium Subscriptions products. Headquartered in Silicon Valley, LinkedIn has offices across the globe..

Founded in 2003, LinkedIn connects the world's professionals to make them more productive and successful. With more than 1 billion members worldwide, including executives from every Fortune 500 company, LinkedIn is the world's largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions and Premium Subscriptions products. Headquartered in Silicon Valley, LinkedIn has offices across the globe..
Founded: 2003 (launched May 2003; company formed Dec 2002)
Headquarters: Sunnyvale, California
Members: Over 1 billion
Employee count: Approximately 26,000 (source snapshot)
Revenue streams: Talent Solutions, Marketing Solutions, Sales Solutions, Premium Subscriptions
Professional networking, recruiting, sales enablement, and professional learning.
2003
Software Development
$12.8M
Reported previously rumored $12.8M round
$53M
Investors included Sequoia, Greylock, Bessemer and Bain Capital Ventures; reported ~ $1B valuation
$22.7M
Follow-on infusion from strategic investors including SAP, Goldman Sachs, and McGraw‑Hill
“Sequoia Capital, Greylock Partners, Bessemer Venture Partners, Bain Capital Ventures and strategic investors (SAP, Goldman Sachs, McGraw‑Hill) participated in private rounds prior to IPO.”
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Sr. Staff Software Engineer, AI Infra
Company Descriptio
n
LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun where everyone can succee
**d.
Job Descript**
ion
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 t
eam.
Join u s to push the boundaries of scaling large models toge ther. The team is responsible for scaling LinkedIn's AI model training, feature engineering and serving with hundreds of billions of parameters models and large-scale feature engineering infra 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 to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, vLLM, HuggingFace, DeepSpeed etc.) in the team. Additionally, this team focused on technologies like LLMs, GNNs, Incremental Learning, Online Learning and Serving performance optimizations across billions of user que
**ries.
Model Training Infrastru** cture: As an engineer on the AI Training Infra t eam, you will play a crucial role in building the next-gen training infrastructure to power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like HuggingFace, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like model parallelism, tensor parallelism, Zero++ etc. Finally, you will assist in and guide the development of containerized pipeline orchestration infrastructure, including developing and distributing stable base container images, providing advanced profiling and observability, and updating internally maintained versions of deep learning frameworks and their companion libraries like Tensorflow, PyTorch, DeepSpeed, GNNs, Flash Attention. PyTorch Lightning and more and
**more.
Model Serving Infrastru** cture: this team builds low latency high performance applications serving very large & complex models across LLM and Personalization models. As an engineer, you will build compute efficient infra on top of native cloud, enable GPU based inference for a large variety of use cases, Cuda level optimizations for high performance, enable on-device and online training. Challenges include scale (10s of thousands of QPS, multiple terabytes of data, billions of model parameters), agility (experiment with hundreds of new ML models per quarter using thousands of features), and enabling GPU inference at
scale.
As a Sr. Staff Software En gineer, you will have first-hand opportunities to advance one of the most scalable AI platforms in th e world. At the same time, you will work together with our talented teams of researchers and engineers to build your career and your personal brand in the AI i
**ndustry.
Responsi**
bilities:
Owning the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended
problems.Designing, implementing, and optimizing the performance of large-scale distributed serving or training for personalized recommendation as well as large langua
ge models.Improving the observability and understandability of various systems with a focus on improving developer productivity and system s
ustenance.Mentoring other engineers, defining our challenging technical culture, and helping to build a fast-gro
wing team.Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., vLLM, PyTorch, GNNs, DeepSpeed, HuggingFa
ce, etc.).Functioning as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI
**Platforms.
Qual**
ifications:
MS or PhD in Computer Science or related technical
discipline.10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leaders
hip position10+ years of experience in an object-oriented programming language such as Python, C++, Java, Go,
Rust, Scala5+ years of experience with large-scale distributed systems and client-server a
rchitecturesExperience building ML applications, LLM serving,
GPU serving.Co-author or maintainer of any open-sou
rce projectsExpertise in machine learning infrastructure, including technologies like MLFlow, Kubeflow and large-scale distrib
uted systemsExpertise in deep learning frameworks and tensor libraries like PyTorch, Tensorfl
**ow, JAX/FLAX
Sugg**
ested Skills:
ML Algorit
hm DevelopmentMachine Learning and
Deep LearningInformation retrieval / recommen
dation systemsTechni
cal leadership
LinkedIn is committed to fair and equitable compensa
tion practices.The pay range for this role is $198,000 to $326,000. 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.linked
**in.com/benefits.
Addit**
ional Info rmation
Team Name: The Search and Fe
ed Federation Team
Team Description: The Search & Feed Federation team is hiring a Sr. Staff Software Engineer to lead the design and development of a next-generation, high-performance orchestrator powering LinkedIn’s Search and Feed systems. Operating at massive scale (100K–1M+ QPS, Tier-1 availability), this role is central to delivering fast, relevant, and reliable content to ever
y LinkedIn member.
This engineer will define and drive the technical vision for a highly extensible federation platform, establish clear API and contract boundaries with product and business teams, and guide the architecture across multiple orgs. The first six months will emphasize understanding requirements, creating the system vision, and driving foundational architectural work, followed by meaningful hands-on engineering and ope
rational ownership.
Success requires deep experience building P0/P1 platform infrastructure and orchestrators at large-scale companies, strong architectural leadership, and the ability to influence senior stakeholders across Search, Feed, and Infrastructure teams. This role partners closely with existing Senior Staff/P-Staff engineers to shape the future of LinkedIn’s core conte
**nt delivery systems.
Equal O**
pportunity Statement We seek candidates with a wide range of perspectives and backgrounds, and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other leg
**ally protected class.
Pay Transpar**
ency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://ln
**kd.in/paytransparency.
Global Data Privacy Not**
ice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedi
n.com/ca
ndidate-portal.Lo
cationMountain
View, CAWorkplace Type