We are seeking collaborative and result-oriented machine learning engineers with both strong experience and a keen interest in taking fundamental research into new product innovation. We expect our machine learning engineers to understand state-of-the-art research and apply it to solve deep technical challenges by distilling research insights into application. As part of our team, you will both conduct experiments and play a key role in developing and scaling the technology for a wide user base.
Lab Summary
We are NEON, a subsidiary of Samsung dedicated to creating Artificial Humans who interact with you in ways indistinguishable from the real world. Our NEONs (Neo humaNs) draw inspiration from the most natural of interfaces: interaction with another human being. Bringing together a world-class R&D team of researchers, developers, and engineers, that are building production technology at the forefront of artificial intelligence, machine learning, real-time computing, conversational agents, computer graphics, design, and more.
NEONs hold the potential to advance our digital world while preserving the elements of human interaction that are meaningful to all of us. If you share that dream – if you want to make the visions you saw in Her, Blade Runner, and more into tangible reality – and are passionate about taking such ideas into handcrafted renderings, we would love to hear from you!
Responsibilities
- Design and build data-driven conversation models with emphasis on realism and natural flow
- Analyze and evaluate the quality of a human-NEON conversation and suggest ways to improve it
- Efficiently conduct experiments to validate conversational AI algorithms with respect to product goals
- Collaborate with researchers, other developers, and the product team to take research ideas into well-thought-out product features
- Collect and curate training data, train models, and optimize them for deployment
- Be a champion of engineering excellence and propose systematic changes to achieve it
Requirements
- 3+ years of experience building end-to-end NLU, NLP or conversational AI systems in a production environment
- Deep understanding of Transformers, Large Language Models (LLMs) and their applications
- Knowledge of conversational design, flow, and natural language generation
- Familiarity with conversational AI/search tools such as RASA, SpaCy, Amazon Lex, Amazon Kendra, or DialogFlow
A Little Extra!
- Fluent in one of the popular Deep Learning frameworks (e.g., Pytorch or Tensorflow)
- Experience with C++