Principal Applied Scientist – Conversational AI & NLU

Socket.dev; Santa Clara (CA); On-site; USD 229,000 - 309,000; Full time

Job summary

Socket.dev is seeking a Principal Applied Scientist with a strong machine learning background to build industry-leading Conversational AI systems. You will develop novel algorithms for NLU, Dialog Systems, and Generative AI with LLMs, collaborating with international experts to push the state of the art and impact millions of users.

The role entails translating customer needs into research problems, mentoring junior scientists, and delivering scalable ML solutions on large-scale data and compute

Qualifications

• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field.
• 5+ years hands-on predictive modeling and analysis experience.
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.
• Experience programming in Java, C++, Python or related language.
• Experience with leading experienced scientists as well as mentoring junior members.

Responsibilities

• Develop novel algorithms and modeling techniques for Conversational AI, NLU, and Generative AI with LLMs.
• Advance state-of-the-art language technology and contribute to modeling research.
• Collaborate with global experts and scale experiments on large computing resources.
• Translate customer needs into concrete research problems and deliver impactful results.

Skills

Predictive modeling

Analytics

Mentoring

Ambiguity handling

Education

PhD in Electrical Engineering / CS / Mathematics

Tools

Java

C++

Python

Job description

Socket.dev is seeking a Principal Applied Scientist with a strong machine learning background to build industry-leading Conversational AI systems. You will develop novel algorithms for NLU, Dialog Systems, and Generative AI with LLMs, collaborating with international experts to push the state of the art and impact millions of users.

The role entails translating customer needs into research problems, mentoring junior scientists, and delivering scalable ML solutions on large-scale data and compute