Staff AI Software Engineer
3 weeks ago
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Senior Talent Acquisition Partner @LinkedInLinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.
This position is based in Dublin, Ireland.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can work from home and commute to a LinkedIn office, depending on what's best for you and when it is important for your team to be together. This is a full-time engineering role based in Dublin, Ireland.
At LinkedIn, our Foundational AI Technologies (FAIT) organisation stands as the innovation epicentre, addressing the fundamental AI challenges and the force behind LinkedIn's next-generation AI-driven member experiences. Our mission spans across the entire marketplace, leveraging our expertise in data curation, algorithm development, and robust infrastructure to spearhead AI innovations. We are dedicated to creating a transformative impact on all LinkedIn products, establishing the platform as a leader in the AI realm.
As a Staff Engineer in the Foundational AI Technologies team, you will act as a domain expert, and you will research, develop, build and ship cutting-edge AI technologies. You are expected to provide technical leadership, and drive architectural decisions and implementation.
This individual will be a core member of LinkedIn's Foundational AI Technologies team and will partner closely with other verticals in Data and AI, and Infrastructure teams. This is a rare opportunity to lead initiatives at the cutting-edge of Data and AI, which benefits every product and team at LinkedIn and over 1 Billion members of the global workforce.
Responsibilities:- Work with BIG data, crunching millions of samples for statistical modelling, data mining, recommendation solutions.
- Write production quality code and influence the next generation of LinkedIn's system.
- Develop and implement Foundation Large Language Model technology, customising it to uniquely comprehend LinkedIn's diverse marketplace entities.
- You will act as the primary domain expert to influence technology choices.
- You will research and develop cutting-edge AI technologies.
- You will build and ship scalable software for AI tasks.
- You will partner effectively with leads (ICs and managers) from other AI teams.
- Lead by example to build a culture of craftsmanship and innovation.
- BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience.
- 4+ years of industry experience in software design, development, and algorithm-related solutions.
- 4+ years experience programming languages such as Java, C/C++, Python, etc.
- 1+ years in an architect or technical leadership position.
- PhD in Computer Science, Machine Learning, Statistics or related fields.
- 5+ years of experience in AI/Data Science.
- Strong academic credentials with publications in top-tier journals and conferences.
- Experience in building large scale AI models and systems.
- Experience in large language models and deep neural network solutions.
- Demonstrated ability to work with peers in engineering across teams to set technical directions.
- Excellent communication and presentation skills.
- Experience building scalable AI innovations with foundation and infra partners.
- Experience with Spark, Tensorflow and Java.
- Previous leadership or mentorship experience is preferred.
- Ability to diagnose technical problems, debug code, and automate routine tasks.
- Analytical approach coupled with solid communication skills and a sense of ownership.
- Deep learning
- Machine learning
- Large language models
- Data Science
- Information Retrieval
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