The Core Recommendation Ranking team in Microsoft AI Content Org powers the end-to-end ranking and reranking stack behind Microsoft’s content experiences , including news, interest, video, and AI-generated content (AIGC) feeds, reaching hundreds of millions of users worldwide.
\nWe are at the forefront of integrating Generative AI and agentic systems into large-scale recommendation pipelines. We are seeking a Senior Applied Scientist to design, build, and optimize ranking and recommendation models that directly impact user engagement across Microsoft’s content ecosystem.
\nIn this role, you will work hands-on with cutting-edge deep learning and LLM-enhanced ranking systems while collaborating closely with engineering and product partners to deliver production-quality solutions at scale.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nDesign & implement ranking, reranking, and retrieval models using deep learning, LLMs, and advanced recommendation techniques.
\nOwn end-to-end ML pipelines , feature engineering, model training, offline/online evaluation, and production inference optimization.
\nInnovate by applying state-of-the-art methods including LLM-enhanced ranking, contextual bandits, reinforcement learning, and generative recommendation approaches.
\nCollaborate cross-functionally with engineering, product, and platform teams to translate research insights into shipped features.
\nContribute to technical direction within the team , propose experiments, identify opportunities, and drive projects from ideation to production.
\nMentor less experienced scientists and engineers, fostering a culture of technical excellence and knowledge sharing.
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\nWe are at the forefront of integrating Generative AI and agentic systems into large-scale recommendation pipelines. We are seeking a Senior Applied Scientist to design, build, and optimize ranking and recommendation models that directly impact user engagement across Microsoft’s content ecosystem.
\nIn this role, you will work hands-on with cutting-edge deep learning and LLM-enhanced ranking systems while collaborating closely with engineering and product partners to deliver production-quality solutions at scale.
\nResponsibilities:
\nQualifications:
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\nCopilot Security and Privacy is responsible for building these defenses directly into Copilot. Our work focuses on new security primitives for agentic AI, including runtime misuse detection, adaptive guardrails, containment and isolation mechanisms, and feedback-driven control systems informed by offensive security research.
\nWe are hiring a Principal Technical Program Manager (TPM) to own the end-to-end delivery of these capabilities. This is a deeply technical execution role for someone who can operate at the boundary of security engineering, AI research, and platform systems,turning ambiguous threat models into shippable, operable defenses deployed in a globally scaled AI product.
\nThis role is not about process, governance, or coordination. The TPM is accountable for making complex systems land in production, under real-world adversarial pressure. Most security roles protect systems after they exist. This role helps define how agentic AI systems defend themselves while they operate.
\nYou will shape how Copilot detects misuse, enforces boundaries, and recovers safely in real time,working directly on the mechanisms that make autonomy deployable at global scale. The impact is immediate, technical, and measurable in production behavior.
\nIf you want to operate where AI systems, security engineering, and execution reality intersect, this role offers that surface area,without turning you into a policy owner or process layer.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nStarting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
\nResponsibilities:
\nOwn Delivery of In-Product AI Threat Defenses
\nLead execution of runtime threat defense capabilities embedded directly into Copilot execution paths, not layered on externally.
\nDrive delivery of detection, prevention, and containment mechanisms that operate synchronously and adaptively as agents reason and act.
\nEnsure defenses are designed as control systems with clear signals, enforcement points, and feedback loops.
\nTranslate Threat Models into Executable Systems
\nTake emerging and ambiguous agentic AI threat models,including misuse, escalation, and information-flow risks,and convert them into concrete engineering plans.
\nPartner with security engineers and researchers to translate offensive security insights and red-team findings into production features.
\nMake judgment calls about enforcement boundaries, degradation strategies, and isolation guarantees.
\nDrive Cross-Cutting Technical Execution
\nCoordinate delivery across security engineering, AI research, platform/runtime teams, and Copilot product surfaces.
\nOwn dependency management, sequencing, and delivery risk for systems that are tightly coupled and cannot be built independently.
\nResolve technical and organizational tradeoffs where ownership boundaries are unclear and failure modes are novel.
\nEnsure Operability at Runtime
\nDefine what “working” means for threat defenses: detection quality, false-positive tolerance, performance impact, and blast-radius containment.
\nEnsure defenses are measurable, testable, and observable in production.
\nLead learning loops from live incidents, near-misses, and adversarial testing back into system design.
\nQualifications:
\nRequired Qualifications:
\nBachelor’s Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
\n3+ years of experience managing cross-functional and/or cross-team projects.
\nPreferred Qualifications:
\nBachelor’s Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.
\nProven ability to lead execution in high-ambiguity environments where requirements, threats, and system behavior evolve rapidly.
\nSolid systems thinking: ability to reason about execution paths, failure modes, and adversarial behavior.
\nTrack record of making sound technical tradeoffs and shipping durable solutions without relying on heavy process.
\nBackground in security engineering, distributed systems, applied research, or ML systems prior to or alongside TPM work.
\nExperience delivering runtime detection, abuse prevention, or adaptive enforcement systems.
\nFamiliarity with agentic AI systems, LLM-based products, or non-deterministic execution environments.
\nExperience partnering closely with offensive security or red-team functions.
\nDemonstrated ability to translate research, prototypes, or threat models into production-grade systems.
\nSolid analytical skills, including working with telemetry, signals, and feedback loops.
\n#MicrosoftAI #MAIDPS
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\nCopilot Security and Privacy is responsible for building these defenses directly into Copilot. Our work focuses on new security primitives for agentic AI, including runtime misuse detection, adaptive guardrails, containment and isolation mechanisms, and feedback-driven control systems informed by offensive security research.
\nWe are hiring a Principal Technical Program Manager (TPM) to own the end-to-end delivery of these capabilities. This is a deeply technical execution role for someone who can operate at the boundary of security engineering, AI research, and platform systems,turning ambiguous threat models into shippable, operable defenses deployed in a globally scaled AI product.
\nThis role is not about process, governance, or coordination. The TPM is accountable for making complex systems land in production, under real-world adversarial pressure. Most security roles protect systems after they exist. This role helps define how agentic AI systems defend themselves while they operate.
\nYou will shape how Copilot detects misuse, enforces boundaries, and recovers safely in real time,working directly on the mechanisms that make autonomy deployable at global scale. The impact is immediate, technical, and measurable in production behavior.
\nIf you want to operate where AI systems, security engineering, and execution reality intersect, this role offers that surface area,without turning you into a policy owner or process layer.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nStarting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
\nResponsibilities:
\nOwn Delivery of In-Product AI Threat Defenses
\nLead execution of runtime threat defense capabilities embedded directly into Copilot execution paths, not layered on externally.
\nDrive delivery of detection, prevention, and containment mechanisms that operate synchronously and adaptively as agents reason and act.
\nEnsure defenses are designed as control systems with clear signals, enforcement points, and feedback loops.
\nTranslate Threat Models into Executable Systems
\nTake emerging and ambiguous agentic AI threat models,including misuse, escalation, and information-flow risks,and convert them into concrete engineering plans.
\nPartner with security engineers and researchers to translate offensive security insights and red-team findings into production features.
\nMake judgment calls about enforcement boundaries, degradation strategies, and isolation guarantees.
\nDrive Cross-Cutting Technical Execution
\nCoordinate delivery across security engineering, AI research, platform/runtime teams, and Copilot product surfaces.
\nOwn dependency management, sequencing, and delivery risk for systems that are tightly coupled and cannot be built independently.
\nResolve technical and organizational tradeoffs where ownership boundaries are unclear and failure modes are novel.
\nEnsure Operability at Runtime
\nDefine what “working” means for threat defenses: detection quality, false-positive tolerance, performance impact, and blast-radius containment.
\nEnsure defenses are measurable, testable, and observable in production.
\nLead learning loops from live incidents, near-misses, and adversarial testing back into system design.
\nQualifications:
\nRequired Qualifications:
\nBachelor’s Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
\n3+ years of experience managing cross-functional and/or cross-team projects.
\nPreferred Qualifications:
\nBachelor’s Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.
\nProven ability to lead execution in high-ambiguity environments where requirements, threats, and system behavior evolve rapidly.
\nSolid systems thinking: ability to reason about execution paths, failure modes, and adversarial behavior.
\nTrack record of making sound technical tradeoffs and shipping durable solutions without relying on heavy process.
\nBackground in security engineering, distributed systems, applied research, or ML systems prior to or alongside TPM work.
\nExperience delivering runtime detection, abuse prevention, or adaptive enforcement systems.
\nFamiliarity with agentic AI systems, LLM-based products, or non-deterministic execution environments.
\nExperience partnering closely with offensive security or red-team functions.
\nDemonstrated ability to translate research, prototypes, or threat models into production-grade systems.
\nSolid analytical skills, including working with telemetry, signals, and feedback loops.
\n#MicrosoftAI #MAIDPS
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\nCopilot Security and Privacy is responsible for building these defenses directly into Copilot. Our work focuses on new security primitives for agentic AI, including runtime misuse detection, adaptive guardrails, containment and isolation mechanisms, and feedback-driven control systems informed by offensive security research.
\nWe are hiring a Principal Technical Program Manager (TPM) to own the end-to-end delivery of these capabilities. This is a deeply technical execution role for someone who can operate at the boundary of security engineering, AI research, and platform systems,turning ambiguous threat models into shippable, operable defenses deployed in a globally scaled AI product.
\nThis role is not about process, governance, or coordination. The TPM is accountable for making complex systems land in production, under real-world adversarial pressure. Most security roles protect systems after they exist. This role helps define how agentic AI systems defend themselves while they operate.
\nYou will shape how Copilot detects misuse, enforces boundaries, and recovers safely in real time,working directly on the mechanisms that make autonomy deployable at global scale. The impact is immediate, technical, and measurable in production behavior.
\nIf you want to operate where AI systems, security engineering, and execution reality intersect, this role offers that surface area,without turning you into a policy owner or process layer.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nStarting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
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\nWe are at the forefront of integrating Generative AI and agentic systems into large-scale recommendation pipelines. We are seeking a Senior Applied Scientist to design, build, and optimize ranking and recommendation models that directly impact user engagement across Microsoft’s content ecosystem.
\nIn this role, you will work hands-on with cutting-edge deep learning and LLM-enhanced ranking systems while collaborating closely with engineering and product partners to deliver production-quality solutions at scale.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nResponsibilities:
\nQualifications:
\n#MicrosoftAI Applied Sciences IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 – $258,000 per year.
\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
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\nWe're looking for an Engineering Manager, Developer Productivity who leads from deep technical craft. Someone who sets a high bar for platform quality, coaches engineers through hard problems, and partners closely with Engineering, Product, and Design to build systems that actually move the needle.
\nThis is also an explicitly AI-native role. You'll be expected to redesign how your team works, building workflows with AI at the center, and mentoring others to do the same.
\nAbout the role:
\nAs an Engineering Manager, Developer Productivity, you'll:
\nAbout you:
\nRequirements:
\nYou’ll thrive as an Engineering Manager, Developer Productivity if you:
\nOur Core Behaviors:
\nBenefits
\nTemporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.
\nBe you, with us
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\nYour responsibilities will include defining and driving Pinterest's technical strategy for agentic engineering, architecting and shipping production systems, reimagining Pinterest's SDLC, owning developer velocity measurement, serving as technical force multiplier across Platform, Infrastructure, and Engineering Acceleration, and driving engineering-wide adoption.
\nTo be successful in this role, you will need 12+ years of software engineering experience with deep expertise in building developer platforms, internal tooling, or engineering infrastructure that measurably changed how engineers work at scale. You will also need demonstrated hands-on experience designing and shipping agentic AI systems in production, experience working in large-scale monorepos or complex multi-service codebases, and familiarity with agentic development best practices.
\nAs a key technical advisor and delegation point, you will work with the Sr. Director, Engineering Acceleration, VP, Infrastructure, and Chief Architect to shape investment priorities and multi-year technical direction. You will also serve as a trusted partner and primary delegation point for the hardest technical questions facing this organization.
\nThis is a startup-within-a-company opportunity, with a charter that is ambitious, problems that are largely unsolved, and systems that you will build will define how an entire engineering organization operates for years.
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\nZuma is pioneering the future of agentic AI and our focus is to transform the rental market experience for consumers and property manager alike. Our innovative platform is engineered from the ground up to boost operations efficiency and enhance support capabilities for property management business across the US and Canada, a ~$200B market.
\nAs a Staff Engineer, you will help define how humans collaborate with intelligent systems in one of the largest and most underserved industries in the world: property management. You’ll shape the technical foundation of a platform that is not just supporting human workflows, but executing them autonomously through AI agents.
\nThis is a rare opportunity to influence how an entire industry evolves, building tools that transform repetitive operational tasks into seamless, intelligent experiences. Your work will directly contribute to how trust is built between humans and machines, how operations scale without added headcount, and how residents and staff experience a new, AI-powered standard of service.
\nDelightful, trustworthy, and deeply effective. Join us to help lead the AI revolution in multifamily, drive meaningful real-world impact, and be part of reimagining what work can feel like when done side-by-side with intelligent agents.
\nYou will be a cornerstone of our engineering organization, reporting to the VPE. This is a pivotal role where you'll lead critical system rewrites, architect scalable foundations for our AI platform, and establish the technical standards that will shape our engineering culture for years to come.
\nYou'll work at the intersection of cutting-edge LLM technology and practical business applications, creating sophisticated systems that power our AI leasing agent while building self-serve experiences that enable rapid customer onboarding.
\nAs our first US-based engineer, you'll bridge the gap between our product vision and technical implementation. This role offers a rare opportunity to directly influence how we architect the next generation of our platform.
\nYou'll tackle projects like rebuilding our onboarding/configuration system to be self-serve, creating robust analytics infrastructure to measure AI performance, and reimagining our integration framework to connect seamlessly with customer systems.
\nYour work will significantly reduce manual engineering overhead while enabling rapid scaling of our customer base.
\nWhy This Could Be Your Dream Role
\nWhy You Might Want to Think Twice
\nResponsibilities
\nYour Experience Looks Like
\nGuiding Principles
\nOther Benefits
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\nAnthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
\nAbout the Team
\nOur team is organised around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.
\nAbout the role
\nAs a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimisation, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.
\nJoin us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity.
\nResponsibilities:
\nYou may be a good fit if you:
\nStrong candidates may also have:
\nLogistics
\nEducation requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
\nVisa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
\nWe encourage you to apply even if you do not believe you meet every single qualification.** Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
\nYour safety matters to us.** To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
\nHow we're different
\nWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science.
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\nWhat you'll do
\nWhat you need
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