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Artificial Intelligence Researcher
1 month ago
About the Role
ENGINEERINGUK is looking for a highly skilled and inventive Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art ML systems for building large-scale, high-quality conversational assistant systems. As an Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, to be tailored to customer needs.
Key Responsibilities
- Use LLM, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals.
- Innovate new methods for contextual knowledge extraction and information representation, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality.
- Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing and verification.
- Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results.
- Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems.
- Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports.
- Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team.
Requirements
- Experience building machine learning models or developing algorithms for business application.
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms.
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
