研究科学家实习生，欺诈与信任方向

Formulate and investigate a focused research question in adversarial scam detection and prevention.

Develop LLM reasoning and representation-learning methods that combine content, behavioral, or social-network evidence to identify scams and distinguish malicious activity from legitimate behavior.

Research agentic systems that plan investigations, use tools, and synthesize evidence, evaluating both individual decisions and end-to-end effectiveness.

Investigate recursive self-improvement and feedback-driven methods that improve agent strategies, reasoning, or workflows over successive iterations, with controlled evaluation to distinguish genuine gains from overfitting or error amplification.

Design rigorous experiments to evaluate robustness under noisy labels and distribution shift, detection–false-positive trade-offs, and computational efficiency.

Collaborate with research scientists, engineers, and cross-functional partners to prototype promising approaches, assess their applicability to production, and communicate research plans, progress, and results.

Document research findings and, where appropriate, contribute to publications and research that can inform Meta product development.

Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field

Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment

Experience building systems based on machine learning, deep learning methods, or natural language processing

Familiarity with algorithms behind generative model training and common deep learning architectures (Transformers, BERT etc.)

Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP and KDD

Research or project experience in one or more of the following: LLM reasoning, agentic systems and tool use, recursive self-improvement, reinforcement learning, automated evaluation, learning from feedback, behavioral or graph representations, weak supervision, or transfer learning.

Demonstrated software development experience via tech internships, work experience, coding competitions, or widely used contributions in open source machine-learning repositories

Experience working and communicating cross functionally in a fast-paced team environment.

Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results

Meta builds technologies that help people connect, find communities, and grow businesses.

When Facebook launched in 2004, it changed the way people connect.

Apps like Messenger, Instagram and WhatsApp further empowered billions around the world.

Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.

People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

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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.

Learn more about benefits at Meta.

Meta is proud to be an Equal Employment Opportunity 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.

You may view our Equal Employment Opportunity notice here.

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You may view our Equal Employment Opportunity notice here.

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.

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Currently has or is in the process of obtaining a Ph.D.

degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field.