Senior Performance Software Engineer

LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. We’re much more than a digital resume -- we transform lives through innovative products and technology.
Every day, millions of posts, videos, and articles course through the LinkedIn feed, generating tens of thousands of comments every hour — and tens of millions more shares and likes.
Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with and lead highly experienced and passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
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.
Develop advanced embedding models (text, graph, structured data) to capture semantic meaning of companies, people, and signals for retrieval and ranking.
- Deploy and monitor production ML pipelines for embedding generation, model inference, and continuous retraining with real-world feedback loops.
- Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
- Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
- Represent LinkedIn in academic and industry circles by showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market
Master’s degree OR Bachelor’s degree with 5+ years of work experience
- 5+ years of experience in at least one of the following areas: Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.

D. in computer science, statistics, engineering, mathematics, or similar quantitative discipline
- 5+ years of hands-on experience working on Recommendation systems, Machine Learning, Statistical modeling/inference, Data mining, Graph/geometric deep learning, Large Language Models, Generative AI, Distributed Training.
- Understanding of standard programming and software engineering practices
- Proven track record of publishing at academic and industry venues
- Machine Learning
- Generative-AI
- Large Language Models
That is why we offer generous health and wellness programs and time away for employees of all levels.
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