Staff Software Engineer, Machine Learning

LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume—we transform lives through innovative products and technology.

LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion-dollar verticals at LinkedIn. The LSS AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform that empowers tens of millions of companies to connect with their future customers and drive significant economic value.

We are looking for an Staff Machine Learning Engineer to play a pivotal role as a technical leader within the LSS AI team. This role goes beyond building models—you will set the technical direction, own the AI roadmap, and lead initiatives that push the boundaries of what’s possible in enterprise AI. 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:
- Lead the design, development, and deployment of state-of-the-art ML systems across search, recommendations, generative AI, reinforcement learning, and LLMs for Sales Navigator.
- Define and drive the technical roadmap and architecture for end-to-end AI systems within LSS, ensuring scalability, reliability, and innovation.
- Research, fine-tune, and adapt large language models (LLMs) and build agentic AI systems that enable reasoning, planning, and decision-making for sales professionals.
- Partner with product, design, and other engineering teams to align AI solutions with business strategy and maximize impact.
- Drive cross-functional collaborations with horizontal AI and platform teams to leverage foundational tools and scale adoption of innovations across LinkedIn.
- Mentor and guide engineers, fostering a culture of craftsmanship, innovation, and technical excellence.
- Represent LinkedIn in external venues (papers, conferences, workshops) by showcasing advances in applied AI research and engineering.

Basic Qualifications:
- MS/PhD degree in Computer Science or related technical discipline, or equivalent practical experience.
- 8+ years of experience in machine learning, artificial intelligence, or related fields.
- 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
- Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
- Expertise in at least one of: LLMs, generative AI, search/recommendations, reinforcement learning, or large-scale deep learning.

Preferred Qualifications:
- 10+ years of experience building and scaling machine learning systems in production.
- Proven experience in pre-training and fine-tuning LLMs, including domain-specific adaptations.
- Strong software engineering skills (Python, Java, C++, or similar), with the ability to design robust, scalable systems.
- Track record of influencing product and technical strategy through AI/ML innovation.
- Publications, patents, or open-source contributions in machine learning, NLP, or related areas.

Suggested Skills:
• Machine Learning
• Large Language Models
• Generative AI
• Search & Recommendations
• Reinforcement Learning
• Technical Leadership
• Cross-Functional Collaboration

You Will Benefit from Our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

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