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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Staff Software Engineer, Machine Learning - **Company:** LinkedIn Corporation - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $191,000.0 - $315,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Python (Programming Language), Machine Learning, Open Source Technology, Recommender Systems, Tensorflow, Azure Machine Learning, Software Safety, AI Infrastructure, Reinforcement Learning, Pytorch, Large Language Models, Model Validation, Generative AI, Information Technology, Machine Learning Operations - **Published:** May 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=99d761e585ec74da ## About the Role Do you have a Bachelor's degree?, * 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, fine-tuning, distilling/compressing, and deploying LLMs in production. * Track record applying LLMs to recommender systems and language agents. * Demonstrated leadership in red-teaming (manual + automated), safety benchmarking/evaluations, content safety/guardrails, prompt-injection/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 safety-first architectures (evaluation pipelines, moderation services, policy engines, incident response & telemetry) for distributed, real-time ML systems. * Strong understanding of RL (e.g., RLHF/RLAIF, offline/online RL) for language-based agents, including safety-aware 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 top-tier publications (NeurIPS, ICLR, ICML, ACL) and/or impactful open-source 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, self-reflection, program synthesis, symbolic/neuro-symbolic methods, search-augmented reasoning, verification-aware decoding). Suggested Skills: * GenAI Safety & Risk: Red-Teaming, Safety Benchmarking/Evaluation, Content Safety & Guardrails, Jailbreak/Prompt-Injection 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: Real-Time ML Services, Safety Policy Engines, Evaluation Pipelines * Technical Leadership: Mentorship, Cross-Functional Collaboration, Roadmapping, Research Direction * Core Tools: Python, PyTorch, Safety Evaluation Tooling ## Description 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 LinkedIn's Responsible AI & Governance (RAI-G) organization, with a mission to set the gold standard for AI safety across all AI applications company-wide. We ensure that every generative AI product is developed and deployed responsibly, ethically, and securely. By combining rigorous governance with cutting-edge 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 company's 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 company's generative AI safety direction. Define the roadmap for safety alignment research, model evaluation, and system-level protections. * Lead AI Safety Research & Innovation: Guide LinkedIn's research agenda in alignment, robustness, and responsible model behaviors. Stay ahead of academic and industry advances, rapidly translating insights into practical, production-ready solutions. * Design Safety-First Foundations: Provide architectural leadership for scalable safety systems-benchmarking, red-teaming, content safety, privacy-preserving training, and real-time guardrails - ensuring they are reliable, performant, and deeply integrated into AI infrastructure. * Deliver High-Impact Solutions in Ambiguous Spaces: Tackle LinkedIn's toughest ethical, regulatory, and risk-driven 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. * Cross-Functional Leadership: Collaborate with Legal, Compliance, Privacy, Infra, and Policy teams to operationalize safety requirements, translate regulatory guidance into technical specifications, and ensure end-to-end 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. * Company-Wide Impact: Ensure safety techniques, tools, and evaluations are deployed across all GenAI products, safeguarding member trust while enabling safe, scalable innovation., LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation. Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36 Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: * Documents in alternate formats or read aloud to you * Having interviews in an accessible location * Being accompanied by a service dog * Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. ## Related Videos - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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