Job ID: 2603015 | Evi Technologies Limited
The Artificial General Intelligence team (AGI) has an exciting position for a Senior Applied Scientist with a strong background in Machine Learning and Large Language Models to play a critical role in driving the deployment of state-of-the-art conversational systems.
As part of this team, you will collaborate with talented scientists and software engineers to enable conversational assistants capabilities to support the use of external tools and sources of information, and develop novel reasoning capabilities to revolutionise the user experience for millions of Alexa customers.
Key Job Responsibilities
As a Senior Applied Scientist, you will lead the development of innovative solutions to large and complex problems. You will use your technical expertise to develop and deploy novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyse customer behaviours and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences, including through presentations and written reports and external publications. You will mentor and guide junior scientists and contribute to the overall growth and development of the team. BASIC QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field Experience with neural deep learning methods and machine learning Experience in building machine learning models for business application Experience in applied research Experience programming in Java, C++, Python or related language Experience in patents or publications at top-tier peer-reviewed conferences or journals PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Posted:
December 19, 2024 (Updated 5 days ago)
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As a Senior Applied Scientist, you will lead the development of innovative solutions to large and complex problems. You will use your technical expertise to develop and deploy novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyse customer behaviours and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences, including through presentations and written reports and external publications. You will mentor and guide junior scientists and contribute to the overall growth and development of the team. BASIC QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field Experience with neural deep learning methods and machine learning Experience in building machine learning models for business application Experience in applied research Experience programming in Java, C++, Python or related language Experience in patents or publications at top-tier peer-reviewed conferences or journals PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Posted:
December 19, 2024 (Updated 5 days ago)
#J-18808-Ljbffr
