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.
This role will be hybrid in LinkedIn's Mountain View campus.
Our team is looking for a frontline manager to manage the data engineering team responsible for AI model experimentation, balancing the building of signal pipelines while optimizing the experiment development lifecycle. This person will manage a small team of engineers and collaborate closely with other data engineers working on other parts of the inference stack, as well as partners in AI, data science, and the information retrieval platform.
The ideal candidate has a strong tech background in large-scale AI recommendation systems, a passion for engineering craft and operational excellence, a track record of adapting to fast-changing technology, and experience growing engineers.
Responsibilities:
Build inference experiments, with the challenge of sparse signals, to improve content recommendations for new members, a critical project that has the attention of the CEO. Collaborate with other data engineers to enhance the inference stack in the process.
Partner with data scientists to innovate and build model evaluation tools based on a variety of data sets. This is an initiative that receives regular attention from VPs.
Work with a crack team of engineers across AI, data science, AI infrastructure, and data engineering to build a state-of-the-art Feed recommendation system that will transform how we do AI at LinkedIn