Meta
The Monetization GenAI Model Capability Team is responsible for all reinforcement learning applications across Monetization GenAI. We conduct state-of-the-art industry research in reinforcement learning to bridge the gap between theoretical reinforcement learning and real-world problems in generative AI models for monetization purposes. At Meta, MGenAI is a top-priority company initiative that requires the customization of off-the-shelf GenAI models. This involves significant investment to tailor these models to meet our specific needs and drive business value. Our mission is to provide industry-leading, easy-to-use, and effective alignment algorithms for MGenAI applications. In this role, you will be working closely with our AI specialists to research and apply SOTA reinforcement learning algorithms on language models and diffusion models. We are seeking Research Scientists to help us with a mission to bring reinforcement learning to large-scale real-world GenAI applications. Our Research Scientists have an opportunity to work with top researchers in applied reinforcement learning to conduct industry research on reinforcement learning algorithms with a goal to achieve a better algorithm, design an algorithm in real-world applications, and apply their ideas at an unprecedented scale.
Responsibilities:
Perform research to advance the science and technology of machine learning and reinforcement learning.
Devise better data-driven models of human behavior.
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Apply state of the art reinforcement learning technologies to achieve production impact in GenAI applications.
Contribute to publications and open-sourcing efforts.
Minimum Qualifications:
Currently has, or is in the process of obtaining, a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Currently has or is in the process of obtaining a PhD in the field of Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Experience in Python, C++, Java or other related languages.
Experience with Deep Learning frameworks such as Pytorch or Tensorflow.
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred Qualifications:
Experience with reinforcement learning in applied areas beyond simple simulators.
Demonstrated experience in solving analytical problems using quantitative approaches.
Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
Experience building systems based on machine learning, reinforcement learning, and/or deep learning methods.
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences.
Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
Experience working and communicating cross-functionally in a team environment.
Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
Compensation:
$117,000/year to $173,000/year + bonus + equity + 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. 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 accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the
Accommodations request form . Apply for this job and take the first step toward a rewarding career at Meta.
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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. 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 accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the
Accommodations request form . Apply for this job and take the first step toward a rewarding career at Meta.
#J-18808-Ljbffr