Research Engineer - AI Safety Systems and Guardrails
We are seeking an experienced Research Engineer to join the System Safety team within Product & Applied Research org at Meta Superintelligence Labs. This role will focus on researching and developing advanced machine learning models, novel algorithms, and scalable systems that improve the safety of Meta's AI products, including Meta AI and conversational, multimodal, and agentic experiences.You will bring current AI safety research into practical product safeguards, with a primary focus on guardrails, policy-adaptable risk detection, adversarial robustness, and safe agent behavior. This is a hands-on technical leadership role with end-to-end ownership of a significant safety area—from setting research direction and developing methods through rigorous evaluation, cross-team integration, and continuous improvement in production.
Research Engineer - AI Safety Systems and Guardrails Responsibilities:
Research and develop state-of-the-art machine learning models and novel algorithms for AI safety, with a primary focus on guardrails, risk detection, policy adherence, and adversarial robustness
Design, prototype, and implement safety systems for language models, multimodal models, and AI agents, addressing harmful assistance, jailbreaks, prompt injection, unsafe tool use, and unauthorized information disclosure across individual interactions and complete agent tasks
Set the technical direction and research roadmap for a significant system safety area, leading complex initiatives across research, alignment, evaluation, product, and infrastructure teams
Architect and optimize reusable safety components and machine learning pipelines, combining learned detection with explicit runtime controls and delivering scalable, low-latency safeguards for real-world applications
Develop high-quality training data, synthetic and adversarial examples, and representative benign cases
conduct rigorous experimentation, ablation studies, and independent held-out evaluation to improve safety, generalization, and robustness
Measure the effectiveness of safeguards within the fully deployed system, balancing risk reduction with false refusals, legitimate task completion, privacy, latency, cost, and reliability
Collaborate closely with model researchers, product managers, engineers, and evaluation, security, and policy partners to translate product needs and safety requirements into validated, production-ready solutions
Monitor, maintain, and iterate on deployed safety models and systems, using approved data and privacy-preserving workflows to identify emerging failure patterns, create regression tests, and drive lasting system or model improvements
Stay at the forefront of research and industry trends in AI safety, LLMs, multimodal modeling, adversarial robustness, and agentic systems
reproduce, critically evaluate, and extend promising methods for product deployment. Mentor engineers and researchers to influence architecture and research decisions, and communicate findings through technical documentation, internal presentations, and external publications where appropriate
Minimum Qualifications:
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Proven track record of research in one or more of the following areas: AI safety, deep learning, adversarial robustness, language models, multimodal machine learning, or agentic AI, demonstrated through original or materially improved methods and rigorous experimental evidence
3+ years of experience in deploying machine learning models and systems at scale in an industry setting
Demonstrated up-to-date expertise in relevant machine learning research advancements, including the ability to reproduce, critically evaluate, and adapt emerging methods to real-world systems
Hands-on programming experience in Python and deep-learning frameworks such as PyTorch, including developing, training or fine-tuning, debugging, and evaluating machine learning models
Demonstrated experience independently defining technical direction and leading complex research or machine learning initiatives end-to-end, aligning multiple teams and delivering measurable product or platform impact
Proven ability to communicate complex technical concepts, influence cross-functional technical decisions, and mentor engineers or researchers
Preferred Qualifications:
Experience developing AI safety guardrails, policy-adaptable classifiers, reliable model-based judges, or adversarial defenses for deployed AI systems
Expertise in safety data generation, adversarial evaluation, calibration, or in multilingual and multimodal safety modeling
Experience with agent safety, prompt-injection defense, multi-turn risk detection, tool-use controls, or security-informed threat modeling
A strong record of relevant research contributions, such as peer-reviewed publications, adopted open-source methods, or widely used systems supported by rigorous evaluation
Experience with efficient model inference, distillation, cascaded models, or distributed ML systems under latency, throughput, cost, and reliability constraints
About Meta:
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.
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, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/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. Learn more about benefits at Meta.