Senior Staff AI Engineer, AI Algorithm Foundations

Company Description

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.

Job Description

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 based in Sunnyvale, CA.

Our Core AI organization is dedicated to transforming the professional world through innovative artificial intelligence solutions. We aim to enhance the experiences of over a billion members worldwide, enabling them to connect, learn, and grow in unprecedented ways. We develop next generation AI technologies that understand the unique needs of professionals and proactively assist them in achieving their goals.

Core AI is embarking on a groundbreaking initiative to develop agentic models that will redefine how our members interact with the LinkedIn platform. We are building advanced AI agents that exhibit reasoning, planning, and interaction capabilities. These agents will power new features and experiences that anticipate professionals' needs, automate complex tasks, and provide personalized guidance, ultimately shaping the future of work.

Responsibilities:

• This is a Senior Technical Leader role that will provide thought leadership and expert individual contribution for a team of Senior and Staff/Lead AI Engineers; reporting to the Director of the Foundational Algorithms (Core AI) team.
• Lead the development of next-generation recommender systems on top of foundational LLMs.
• Design and train large language models (LLMs) from scratch or adapt existing models to achieve state-of-the-art performance on recommendation tasks in Linkedin’s domain.
• Drive architectural decisions for foundational model development and deployment, ensuring scalability, efficiency, and robustness.
• Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation and excellence.
• Collaborate with cross-functional teams (product engineering, infrastructure) to identify high-impact opportunities and integrate models into the LinkedIn platform.
• Stay at the forefront of research in LLMs and related fields, contributing to the broader research community through publications and presentations.
• Define and execute rigorous evaluation strategies to benchmark the performance of foundational models against state-of-the-art solutions.

Qualifications

Basic Qualifications:

• 2+ years as a Technical Lead, Staff Engineer, Principal Engineer, or equivalent.

• 5+ years of industry experience in AI or Machine Learning Engineering.

• BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience

Preferred Qualifications:

• 10+ years of overall industry/research experience in AI and/or Machine Learning.

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Expert-level understanding of deep learning architectures, particularly Transformer models, and experience training and fine-tuning LLMs and applying them to recommender systems.

• Also, extensive experience developing models with advanced reasoning and planning capabilities.

• Strong programming skills in Python and relevant deep learning frameworks (e.g., PyTorch).

• Significant contributions to the field of AI, demonstrated through publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, ACL) or impactful open-source projects.

• Proven ability to build models that accurately interpret and follow complex, nuanced instructions (zero-shot or few-shot).

• Also, experience developing models that can evaluate their own progress, identify errors, and adjust their approach accordingly.

• Strong understanding of reinforcement learning (RL) techniques and their application to agent training in language-based environments.

• Experience with specific techniques for improving reasoning and planning in LLMs: e.g., program synthesis, symbolic reasoning, neuro-symbolic AI.

Suggested Skills:

• AI Modeling