$ cat jobs/staff-software-engineer-machine-learning-linkedin3-02d1b7800bc5.json
Staff Software Engineer, Machine Learning
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. We're 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 succeed. Join us to transform the way the world works. We are looking for a Staff Machine Learning Engineer to play a pivotal role within the AI team. This role goes beyond building models - you will set the technical direction and lead initiatives that push the boundaries of what's possible. You will combine deep research expertise with the ability to build production-grade ML systems at scale, partnering across engineering, product, and research to deliver transformative AI solutions. 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. Responsibilities Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments. Build and deploy relevance models that power our various recommender systems and personalized intent engines. Explore novel approaches for machine learning ranking and modeling downstream impact, as well as new ways of creating new product features by leveraging the cutting edge machine learning techniques in Generative AI, NLP. Keep scalability and performance in mind through your design and engineering choices. Work directly with partner data science, product, and infrastructure teams to take your ideas from
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