$ cat jobs/software-engineer-machine-learning-linkedin3-58b2c2980151.json
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. 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. The Enterprise AI team is responsible for $7B+ lines of business across Hirer, Learning, and Enterprise Jobs. The Hirer AI team connects individuals to opportunities and is building the next-generation recruiter platform with GenAI-powered tools such as AI-assisted search and automated InMails. A new charter, Hiring Assistant, will revolutionize recruiting workflows and is LinkedIn’s #1 priority. The work in the team includes building, tuning, and applying generative AI models where relevant; working with OpenAI to power GAI applications where relevant; and innovating on cutting-edge search and recommendation models to retrieve the best candidates for a given role. As part of a new and fast-growing team of scientists and engineers, you will experience the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise. 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 recommender systems and personalized in
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