Microsoft Technical Training jobs at Microsoft in United States, New York
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11 jobs found
16.09.2024
M
Microsoft Senior Researcher - Deep Learning & AI – Microsoft Research United States, New York, New York
Pre-training: especially of language models, action models and multimodal models. Alignment andPost-training: e.g., Instruction tuning and reinforcement learning from feedback. Continual Learning: Enabling LLMs to evolve and adapt over time...
Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+years experiencein software development, data modeling or data engineering workORMaster's Degree in Computer Science, Math, Software...
Master's Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 2+years experiencein data analysis and reporting, data science, business intelligence, or business and financial...
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and...
Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+years experiencein business analytics, data science, software development, data modeling or data engineering workORMaster's Degree in...
Bachelor’s degree in computer science, or related technical discipline AND8+ years technical engineering experience buildingteams andapplications with coding in languages including, but not limited to, Python, C#, C++, Rust, Java....
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and...
Pre-training: especially of language models, action models and multimodal models. Alignment andPost-training: e.g., Instruction tuning and reinforcement learning from feedback. Continual Learning: Enabling LLMs to evolve and adapt over time...
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