Research Scientist Intern, AI for Egocentric Representation Learning (PhD)

Meta; Redmond (WA); On-site; USD 125,000 - 150,000; Full time

Job summary

An innovative firm is seeking a Research Scientist Intern to contribute to groundbreaking advancements in AR/VR systems. This role involves developing methods for robust representation learning from multimodal data, collaborating with a talented team, and conducting research that leads to publishable results in top-tier conferences. Candidates should have a strong background in machine learning, particularly in self-supervised and multimodal learning, along with excellent research and interpersonal skills. This internship offers a unique opportunity to work at the forefront of technology and make a significant impact in the field.

Benefits

Health Insurance

Flexible Work Hours

Professional Development

Networking Opportunities

Remote Work Options

Wellness Programs

Employee Discounts

Paid Time Off

Mentorship Programs

Company Events

Qualifications

• Pursuing a PhD in relevant technical fields is required.
• Excellent research skills and proficiency in Python and ML libraries.

Responsibilities

• Develop methods for learning representations from multimodal data.
• Collaborate with researchers and write modular research code.

Skills

Python

Machine Learning

Self-Supervised Learning

Multimodal Learning

Video Understanding

Representation Learning

Research Skills

Interpersonal Skills

Education

PhD in Machine Learning

PhD in Computer Vision

PhD in Applied Statistics

PhD in Computational Neuroscience

Tools

Numpy

Scikit-learn

Scipy

Pandas

Matplotlib

TensorFlow

PyTorch

Job description

Research Scientist Intern, AI for Egocentric Representation Learning (PhD)

Reality Labs Research is looking for an intern to help us develop the next generation assistance systems that guide the users in contextual and adaptive future AR/VR systems. In particular, we are seeking candidates who have experience with either of the following: multimodal learning, self-supervised learning, video understanding, representation learning.

Responsibilities:

1. Develop, implement, and evaluate methods for learning robust representations from multi-modal egocentric data (e.g., video, audio, inertial measurement units).
2. Make use of Meta’s large infrastructure to scale and speed up experimentation.
3. Write modular research code that can be reused in other contexts.
4. Collaborate with other researchers.
5. Work towards taking on big problems and deliver clear, compelling, and creative solutions to solve them at scale.
6. The work should result in publishable research to appear in a top-tier ML or CV conference (e.g., NeurIPS, ICLR, CVPR, ECCV).

Minimum Qualifications:

1. Currently has or is in the process of pursuing a PhD in machine learning, computer vision, speech processing, applied statistics, computational neuroscience, or relevant technical field.
2. Excellent research skills involving defining problems, exploring solutions, and analyzing and presenting results.
3. Proficiency in python and machine learning libraries (numpy, scikit-learn, scipy, pandas, matplotlib, tensorflow, pytorch).
4. Deep understanding of at least one of the following areas: Transfer, few-shot, zero-shot, continual and/or online learning, self-supervised learning, or multi- or cross-modal learning.
5. Interpersonal skills: cross-group collaboration and cross-culture collaboration.
6. Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

1. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CHI, UIST, IMWUT, CVPR, ICCV, ECCV, AAAI, ICRA, SIGGRAPH, ETRA, or similar.
2. Experience with deep metric learning / neural net embedding methods.
3. Experience on vision based input recognition systems, such as hand tracking, body pose estimation.
4. Experience on working with time sequence form sensor data, such as IMU and audio.
5. Experience working and communicating cross functionally in a team environment.
6. Intent to return to degree program after the completion of the internship/co-op.
7. Availability for minimum 16 consecutive week internship.

Compensation:

$7,800/month to $11,293/month + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Equal Employment Opportunity and Affirmative Action:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to [e-mail].