Senior Staff AI Engineer, Network Growth AI

LinkedIn•Mountain View, CA

10d•Hybrid

About The Position

The Network Growth and Relationship AI team is at the forefront of creating cutting-edge, AI-powered solutions that drive meaningful connections and foster professional growth. Our team builds scalable machine learning models and advanced AI systems that help millions of LinkedIn members expand their networks, discover new opportunities, and deepen professional relationships. By leveraging vast data and deploying sophisticated algorithms, we enhance member experience with personalized recommendations, insights, and connections that transform their career paths. Our recommender systems have adopted the latest modeling techniques including Sequence Modeling, LLM, EBR, GNN, etc, and we're continuing our journey as the modeling innovation pioneer at LinkedIn to build both ranking and retrieval models that impact the entire LinkedIn ecosystem. The Network Growth AI team is highly impactful and is in charge of optimizing member value, helping them to build relationships on LinkedIn and advance their professional network. The team works in close collaboration with the product, engineering and data science team and has a very exciting roadmap ahead. If you are looking to lead a highly visible team that operates at a fast pace, works on exciting research problems and delivers great results every quarter, Network Growth AI is the place you should look. We also publish in top machine learning conferences.

Requirements

2+ years of experience as a Technical Lead
5+ years of overall industry experience in AI / Machine Learning
Bachelor’s, Master’s, or PhD Degree in Computer Science, Machine Learning, or related technical discipline or equivalent practical experience

Nice To Haves

10+ years of industry experience.
4+ years of technical leadership (Staff+) experience, including recent experience at the Senior Staff / L7 / Principal Engineer level.
Ph.D. in Computer Science, Machine Learning, Natural Language Processing, or a related discipline.
Prior experience with large scale ML data infrastructure
Experience with developing and designing production scale recommender system products.
Published work in academic conferences or industry circles.

Responsibilities

Leading a team of scientists and machine learning engineers that build and own personalization algorithms, models, and systems.
Leading the core modeling initiatives in the team, including efforts in Generative Recommendation, Large Language Models, Graph Neural Networks, and Sequential Models.
Challenging the status quo on AI, Engineering, and Product fronts, proposing innovative new ideas, and leading these new initiatives to production to further improve member experience and drive value.
Being responsible for the team’s core modeling effort and mid/long term direction.
Actively participating in key technical and design discussions with technical leads in the team.
Collaborating with platform engineering, product, data science and partner teams to design machine learning solutions to power Network Growth ecosystem and optimize member experience.
Operating best engineering and scientific practices & processes to ensure productivity of the team and drive faster iterations via A/B experiments.
Being a role model and professional coach for engineers with a strong bias for action and focus on craftsmanship.
Working with peers across teams to support and leverage a shared technical stack.
Coaching the team to produce high-quality software that is unit tested, code reviewed, and checked in regularly for continuous integration.