Research Scientist Intern, Multimodal and Multitasking Machine Learning (PhD)
Meta
Research Scientist Intern, Multimodal and Multitasking Machine Learning (PhD)
Job Description
Meta’s mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Meta are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started. Meta Reality Labs Research is looking for upcoming scientists and researchers with great interest in algorithm/hardware co-design and acceleration of AI machine learning applications, efficient sensing, and ML algorithms for AR/VR applications. Our team specializes in developing state-of-the-art hardware optimized algorithms for machine perception. With the vision of always-on AI assistance, our team is focusing on cutting edge systems that can facilitate and bring AI assistants powered by LLMs to wearables systems. This internship will focus on aspects of foundational AI technologies around multitasking, multimodal understanding (audio, visual, spatial, etc), privacy, or others that support AI assistant functionalities. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Locations
- Burlingame, CA, USA
Salary
Estimated Salary Rangemedium confidence
8,000,000 - 12,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- algorithm/hardware co-designintermediate
- AI machine learning applicationsintermediate
- efficient sensingintermediate
- ML algorithms for AR/VRintermediate
- hardware optimized algorithmsintermediate
- machine perceptionintermediate
- multitaskingintermediate
- multimodal understandingintermediate
- audio processingintermediate
- visual processingintermediate
- spatial processingintermediate
- privacy in AIintermediate
- AI assistant functionalitiesintermediate
- problem solvingintermediate
- teamworkintermediate
- iterationintermediate
Required Qualifications
- Currently has, or is in the process of obtaining a PhD in the fields of Computer Science, Electrical Engineering, or related field Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment 2+ years research experience in one or more of the following: developing machine learning and computer vision models, optimization of edge computing algorithms, or distributed compute architectures 2+ years experience programming in Python/C++ Experience with Deep Learning frameworks (Pytorch, TensorFlow, etc) Experience in multimodal ML algorithms (object detection, classification, tracking, keyword spotting, ASR, etc) Experience in deploying ML algorithms to real-time with mobile platforms Experience w/ NAS or developing and deploying algorithms with hardware constraints Experience w/ pretraining using self-supervised learning Experience w/ tuning LLM Experience in privacy preserving ML algorithms Proven track record of achieving significant results, as demonstrated by first- and/or co-authored publications at leading workshops or conferences (e.g., CVPR, ICCV, TinyML, NeurIPS, ICML), patents, or grants Intent to return to the degree program after the completion of the internship (experience, 2 years)
Responsibilities
- Research on design / model / execution of efficient ML algorithms Research on novel ML or computational imaging algorithms for applications and optimize existing algorithms Research on development and optimization of edge computing algorithms (ML and non-ML) Collaboration with and support of other researchers across various disciplines Communication of research agenda, progress and results Prototyping, building and characterizing experimental systems and custom hardware
Tags & Categories
Research Scientist Intern, Multimodal and Multitasking Machine Learning (PhD)
Meta
Research Scientist Intern, Multimodal and Multitasking Machine Learning (PhD)
Job Description
Meta’s mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Meta are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started. Meta Reality Labs Research is looking for upcoming scientists and researchers with great interest in algorithm/hardware co-design and acceleration of AI machine learning applications, efficient sensing, and ML algorithms for AR/VR applications. Our team specializes in developing state-of-the-art hardware optimized algorithms for machine perception. With the vision of always-on AI assistance, our team is focusing on cutting edge systems that can facilitate and bring AI assistants powered by LLMs to wearables systems. This internship will focus on aspects of foundational AI technologies around multitasking, multimodal understanding (audio, visual, spatial, etc), privacy, or others that support AI assistant functionalities. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Locations
- Burlingame, CA, USA
Salary
Estimated Salary Rangemedium confidence
8,000,000 - 12,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- algorithm/hardware co-designintermediate
- AI machine learning applicationsintermediate
- efficient sensingintermediate
- ML algorithms for AR/VRintermediate
- hardware optimized algorithmsintermediate
- machine perceptionintermediate
- multitaskingintermediate
- multimodal understandingintermediate
- audio processingintermediate
- visual processingintermediate
- spatial processingintermediate
- privacy in AIintermediate
- AI assistant functionalitiesintermediate
- problem solvingintermediate
- teamworkintermediate
- iterationintermediate
Required Qualifications
- Currently has, or is in the process of obtaining a PhD in the fields of Computer Science, Electrical Engineering, or related field Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment 2+ years research experience in one or more of the following: developing machine learning and computer vision models, optimization of edge computing algorithms, or distributed compute architectures 2+ years experience programming in Python/C++ Experience with Deep Learning frameworks (Pytorch, TensorFlow, etc) Experience in multimodal ML algorithms (object detection, classification, tracking, keyword spotting, ASR, etc) Experience in deploying ML algorithms to real-time with mobile platforms Experience w/ NAS or developing and deploying algorithms with hardware constraints Experience w/ pretraining using self-supervised learning Experience w/ tuning LLM Experience in privacy preserving ML algorithms Proven track record of achieving significant results, as demonstrated by first- and/or co-authored publications at leading workshops or conferences (e.g., CVPR, ICCV, TinyML, NeurIPS, ICML), patents, or grants Intent to return to the degree program after the completion of the internship (experience, 2 years)
Responsibilities
- Research on design / model / execution of efficient ML algorithms Research on novel ML or computational imaging algorithms for applications and optimize existing algorithms Research on development and optimization of edge computing algorithms (ML and non-ML) Collaboration with and support of other researchers across various disciplines Communication of research agenda, progress and results Prototyping, building and characterizing experimental systems and custom hardware
Tags & Categories