Sr. Staff AI Engineer, GenAI Safety

At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team. This role will be based in Sunnyvale CA.

The Generative AI (GenAI) Safety team sits at the heart of LinkedIns Responsible AI & Governance (RAIG) organization with a mission to set the gold standard for AI safety across all AI applications companywide. We ensure that every generative AI product is developed and deployed responsibly ethically and securely. By combining rigorous governance with cuttingedge ML research we identify and mitigate risks such as bias hallucination misuse and privacy leakage.

As both the AI Safety Research team and the central AI safety engineering function we build safety guardrails evaluation pipelines and alignment techniques that enable safe innovation at scale. Our work is foundational to the companys AI strategy and influences standards across the industry. We partner closely with Legal Compliance AI Infrastructure and Product teams to embed safety into every stage of the AI lifecycle.

Responsibilities

• Drive GenAI Safety Strategy: Serve as the senior technical leader shaping the companys generative AI safety direction. Define the roadmap for safety alignment research model evaluation and systemlevel protections.

• Lead AI Safety Research & Innovation: Guide LinkedIns research agenda in alignment robustness and responsible model behaviors. Stay ahead of academic and industry advances rapidly translating insights into practical productionready solutions.

• Design SafetyFirst Foundations: Provide architectural leadership for scalable safety systemsbenchmarking redteaming content safety privacypreserving training and realtime guardrails ensuring they are reliable performant and deeply integrated into AI infrastructure.

• Deliver HighImpact Solutions in Ambiguous Spaces: Tackle LinkedIns toughest ethical regulatory and riskdriven problems. Bring clarity and direction in areas with evolving standards ensuring the company ships safe GenAI experiences at speed.

• Liaison With Product Engineering: Partner closely with product engineering teams to stay current on emerging experiments venture bets and product innovations ensuring safety research and tooling anticipate and support the next wave of product development.

• CrossFunctional Leadership: Collaborate with Legal Compliance Privacy Infra and Policy teams to operationalize safety requirements translate regulatory guidance into technical specifications and ensure endtoend alignment across disciplines.

• Technical Mentorship: Mentor and grow a team of 15 engineers across research ML and systems. Elevate engineering rigor drive high bar execution and nurture future technical leaders in AI safety.

• CompanyWide Impact: Ensure safety techniques tools and evaluations are deployed across all GenAI products safeguarding member trust while enabling safe scalable innovation.

Qualifications :

Basic Qualifications:

• 2 years as a Technical Lead Staff Engineer Principal Engineer or equivalent.

• 5 years of industry experience in AI or Machine Learning Engineering.

• BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience

Preferred Qualifications:

• 10 years of industry and/or research experience in AI/ML delivering impact at scale.

• PhD in CS/AI/ML or related field (or equivalent research/industry achievements).

• Expert understanding of Transformers; hands-on experience training finetuning distilling/compressing and deploying LLMs in production.

• Track record applying LLMs to recommender systems and language agents.

• Demonstrated leadership in redteaming (manual automated) safety benchmarking/evaluations content safety/guardrails promptinjection/jailbreak detection and abuse/misuse prevention.

• Experience translating Legal/Compliance requirements (e.g. EU AI Act) into technical controls including harm taxonomies model cards and risk assessments.

• Proven ability to design safetyfirst architectures (evaluation pipelines moderation services policy engines incident response & telemetry) for distributed realtime ML systems.

• Strong understanding of RL (e.g. RLHF/RLAIF offline/online RL) for languagebased agents including safetyaware reward design and feedback loops.

• Advanced Python and PyTorch; familiarity with TensorFlow.

• Experience with safety evaluation tooling (e.g. platforms akin to LLUME) and safety datasets/benchmarks.

• Significant contributions via toptier publications (NeurIPS ICLR ICML ACL) and/or impactful opensource or widely used safety tooling.

• Proven technical leadership mentoring 15 engineers setting direction and elevating execution quality.

• Effective liaison with Product Engineering (tracking experiments and venture bets; aligning safety research to upcoming bets) and strong collaboration with Legal Compliance AI Infra and Policy.

• Good to have: Experience with advanced reasoning/planning (e.g. CoT/ToT selfreflection program synthesis symbolic/neurosymbolic methods searchaugmented reasoning verificationaware decoding).

Suggested Skills:

• GenAI Safety & Risk: RedTeaming Safety Benchmarking/Evaluation Content Safety & Guardrails Jailbreak/PromptInjection Detection Model Cards & Risk Taxonomies Incident Response & Monitoring

• AI Modeling: LLMs Alignment Reasoning & Planning

• Reinforcement Learning (RL): RLHF/RLAIF Reward Design Feedback Loops Adaptive Systems

• Architecture & Platforms: RealTime ML Services Safety Policy Engines Evaluation Pipelines

• Technical Leadership: Mentorship CrossFunctional Collaboration Roadmapping Research Direction

• Core Tools: Python PyTorch Safety Evaluation Tooling

You will Benefit from our Culture:

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $191000 - $315000. Actual compensation packages are based on a wide array of factors unique to each candidate including but not limited to skill set years & depth of experience certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For additional information visit: Information :

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No

Employment Type :

Full-time