You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes. You will contribute to the development of the next generation of MSN that is adopting the latest generative AI techniques.

Microsoft'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.

Responsibilities: Advance the recommendation & ranking stack. Architect and productionize large-scale DNN/LLM-enhanced recommenders (representation learning, sequence modeling, retrieval/ranking, slate optimization), balancing user satisfaction, content quality, and business goals. Deepen user & content understanding. Gather and analyze user signals from diverse sources to gain a thorough understanding of user behaviors and utilize ML/AI techniques to interpret and predict user needs and preferences. Design and build models that assess content quality and utility aspects to ensure product safety and drive sustainable user engagement. Scale E2E ML/AI systems. Collaborate with engineering on data contracts, feature stores, distributed training/inference, and automated rollout/rollback; drive architectural investments that increase agility and reliability of Discover's AI platform. Drive innovation in AI-forward products. Collaborate with product, science and engineering team closely to innovate in AI-forward products, including agentic content feed experience with hyper personalized AI-generated content and generative UI. Mentor & influence. Provide technical leadership across problem framing, methodology selection, code quality, and publishing/knowledge-sharing; uplevel peers through design reviews, deep-dives, and principled decision-making. Stay close to users. Translate user engagements and behavioral history into model objectives and product bets; ensure our AI solutions elevate relevance, transparency, and engagement for real users.

Qualifications: Required Qualifications: Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Preferred Qualifications: Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 6+ years of industry experience on applied AI/ML for web scale products. Having publications at top AI/ML conferences (e.g., KDD, SIGIR, NIPS, ICML, ICLR, RecSys, ACL, CIKM, CVPR, ICCV, etc.). Demonstrated capability to grow the business through the innovation of ML algorithms. Experience in Software Engineering and familiar with ML Infra.

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Key responsibilities include:

• Architecting the Gemini app serving and orchestration layers, writing design docs, and defining interfaces to ensure the codebase is scalable, modular, and capable of supporting rapid innovation.
• Designing and implementing robust CI/CD pipelines and experimentation platforms, building tooling that enables the wider engineering team to utilize A/B testing and feature flags to safely and quickly iterate.
• Driving application performance initiatives, debugging complex production issues, and advocating for code quality standards to ensure the infrastructure scales to our product needs.
• Acting as the strategic technical counterpart to product and design leadership, assessing feasibility of ambitious concepts, and proposing technical solutions that turn AI capabilities into reality.
• Mentoring staff and senior engineers, leading code reviews, and fostering a culture of technical accuracy, psychological safety, and user-centricity.

In order to set you up for success, we look for the following skills and experience:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical experience.
• 15 years of experience in software engineering, building and working with systems in the technology organization.

In addition, the following would be an advantage:

• Experience building large-scale serving infrastructure.
• Experience implementing observability, telemetry, and real-time monitoring strategies.
• Ability to design and refactor complex server-side architectures that have scaled, ideally at the >1 billion user scale.
• Ability to analyze data to identify bottlenecks and drive technical decisions regarding performance optimizations.
• Ability to unblock teams by solving the hardest technical problems, balancing technical debt with feature work, and driving predictable delivery through architectural clarity.
• Ability to drive technical consensus across multiple teams and stakeholders, translating technical constraints into clear options for leadership.

The US base salary range for this full-time position is between $307,000 - $427,000 + bonus + equity + benefits.

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Artificial intelligence will be one humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.

The Role

As an Engineering Director, you will lead the Create strategy. Teams within Create focus on empowering users to generate and refine various forms of content, from visual media to generative music. The teams also work on developing robust content input and understanding capabilities to seamlessly integrate users' ideas.

In addition to these areas, you will work closely with Product Management, User Experience, and Data Science to improve these features and to build new LLM-forward capabilities into the Gemini App product. You will deploy capabilities that drive daily usage of the product.

To build out these features, each of your areas have a deep connection to Generative AI (Gen AI). You will partner closely with different Gen AI counterparts to quickly bring the latest and greatest model capabilities from Google DeepMind's Gen AI unit into the product.

Your core responsibilities will include:

• Define and execute the overall technical strategy for the Create area within Gemini App, aligning with the broader product outlook and driving daily usage.

• Lead and manage multiple engineering teams focused on features like content input and understanding, and content generation.

• Partner closely with Product Management, User Experience, and Data Science leads to define product roadmaps and deliver new LLM-forward capabilities.

• Drive the integration of GenAI model capabilities into Gemini App products.

• Foster a culture of innovation, collaboration, and rapid iteration within the engineering teams.

• Establish and track key performance indicators for the Create area, focusing on DAU for Gemini App.

• Manage cross-functional dependencies and collaborations with Gen AI, Workspace, Labs, and others as required to deliver great features.

• Ensure the scalability, reliability, and performance of Create-related features.

Candidate Qualifications

In order to set you up for success, we look for the following skills and experience:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical experience.

• 15 years of experience in software engineering, building and working with systems in the technology organization.

• 7 years of experience managing teams of software engineers and managers of software engineers.

In addition, the following would be an advantage:

• Master's or PhD degree in Computer Science, or a related technical field.

• Experience incubating and scaling new product initiatives from conception (0 to 1) to broad adoption in a fast-paced or startup environment.

• Expertise and direct experience in the application and deployment of large-scale AI/Machine Learning systems, particularly in generative AI for consumer products.

Salary

The US base salary range for this full-time position is between $307,000 - $427,000 + bonus + equity + benefits.

Benefits

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law.

If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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Artificial intelligence will be one humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.

We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

The Role:

As an Engineering Director, you will lead the Create strategy. Teams within Create focus on empowering users to generate and refine various forms of content, from visual media to generative music. The teams also work on developing robust content input and understanding capabilities to seamlessly integrate users' ideas. In addition to these areas, you will work closely with Product Management, User Experience, and Data Science to improve these features and to build new LLM-forward capabilities into the Gemini App product.

You will deploy capabilities that drive daily usage of the product. To build out these features, each of your areas have a deep connection to Generative AI (Gen AI). You will partner closely with different Gen AI counterparts to quickly bring the latest and greatest model capabilities from Google DeepMind's Gen AI unit into the product.

Your core responsibilities will include:

• Define and execute the overall technical strategy for the Create area within Gemini App, aligning with the broader product outlook and driving daily usage.

• Lead and manage multiple engineering teams focused on features like content input and understanding, and content generation.

• Partner closely with Product Management, User Experience, and Data Science leads to define product roadmaps and deliver new LLM-forward capabilities.

• Drive the integration of GenAI model capabilities into Gemini App products.

• Foster a culture of innovation, collaboration, and rapid iteration within the engineering teams.

• Establish and track key performance indicators for the Create area, focusing on DAU for Gemini App.

• Manage cross-functional dependencies and collaborations with Gen AI, Workspace, Labs, and others as required to deliver great features.

• Ensure the scalability, reliability, and performance of Create-related features.

Candidate Qualifications

In order to set you up for success, we look for the following skills and experience:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical experience.

• 15 years of experience in software engineering, building and working with systems in the technology organization.

• 7 years of experience managing teams of software engineers and managers of software engineers.

In addition, the following would be an advantage:

• Master's or PhD degree in Computer Science, or a related technical field.

• Experience incubating and scaling new product initiatives from conception (0 to 1) to broad adoption in a fast-paced or startup environment.

• Expertise and direct experience in the application and deployment of large-scale AI/Machine Learning systems, particularly in generative AI for consumer products.

• The US base salary range for this full-time position is between $307,000 - $427,000 + bonus + equity + benefits.

Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

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You will engage directly with users to understand their revenue, billing, and payments requirements. You will translate what you learn into technical solutions and bring that user reality back to product teams. This is a genuinely user-facing role, not user-facing in the "I read a dashboard" sense.

You will build across product boundaries, designing and deploying products and solutions that address product-market fit gaps, not just in Billing but across multi-product boundaries (Payments + Invoicing + Global LPMs). You will embed within Stripe product engineering teams to co-develop the highest-leverage capabilities.

You will build reusable solutions, not one-off fixes. You will contribute to a customization framework for RFA and adjacent products: tailored billing logic, financial workflows, integrations (custom metering, product catalog integrations, checkout flows). You will build patterns and blueprints that scale beyond the individual engagement.

You will provide architectural guidance, reviewing user architectures, advising on best practices, and optimizing integration and performance for complex enterprise environments. You will contribute to a growing library of architectural patterns for the field.

You will resolve critical technical challenges, diagnosing and fixing complex product/engineering problems across the stack. You will identify systemic improvements that prevent recurrence and improve platform stability.

You will inform the product roadmap, the integration gaps, migration friction, and multi-product failures you surface directly shape Stripe's product strategy. You will advocate for what users actually need based on what you've seen firsthand.

You will raise the bar on engineering, improving engineering standards, tooling, and processes within the team. You will help build for sustainability as the team grows.

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What you'll do

Become one of the foremost technical experts for our API and product offerings at Perplexity AI.

• Serve as the dedicated technical resource and advocate for our most important API and product customers, providing in-depth troubleshooting assistance and educating them on optimal use of our platforms.

What you need

• Fluency in English and Japanese is a must

• 7+ years of experience in software engineering or similar roles, with a focus on application development, tooling and automation.

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