微软Senior Software Engineer (AI)
任职要求
Bachelor, Master, PhD degree in CS/EE or related areas is required.3+ years of experience in machine learning, computer vision, VLM, image and video generation and editing. Experience with diffusion models and AI agent is a plus.Proven track record of leading and delivering successful projects in content generation and optimizationProficiency in programming languages with high performance such as: C/C++, Python, C#Excellent problem-solving skills and the ability to think creatively and strategicallyStrong communication skills and the ability to work productively in a collaborative, cross-functional team environment Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
工作职责
Lead the development and evaluation of advanced algorithms and models for content generation, especially image and video processing and generation to ensure high quality and engaging content Optimize and scale existing systems to handle large volumes of data and ensure high performanceConduct research and stay up-to-date with the latest advancements in AIGC, computer vision to ensure our solutions are cutting-edgeAnalyze performance and identify opportunities based on offline and online testing, develop, and deliver robust and scalable solutions, make direct impact to both user and advertisers experienceCollaborate with cross-functional teams, including product managers, designers, and other engineers, to define and execute on the ad content generation strategy.
Design and develop AI-driven applications, delivering scalable, user-focused solutions across web and mobile platforms.Build and maintain robust, cloud-based architectures, ensuring seamless integration of front-end and back-end systems with AI models.Prototype and implement new features, leveraging analytics, user insights, and market trends to improve product quality and user experience.Collaborate with product managers, designers, and data scientists to align technical solutions with product strategies and business goals.Drive technical innovation by exploring new technologies and frameworks, ensuring system performance, maintainability, and scalability.Mentor and support junior engineers, fostering a culture of collaboration, learning, and continuous improvement.
A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and SW/HW teams running AI workload in GPU cluster.As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the performance and efficiency of the system. What you’ll be doing: • Build internal profiling and analysis tools for AI workloads at large scale • Build debugging tools for common encountered problems like memory or networking • Create benchmarking and simulation technologies for AI system or GPU cluster • Partner with HW architects to propose new features or improve existing features with real world use cases
This role requires a blend of skills in software engineering, machine learning, and operations to ensure the smooth functioning of ML systems in production environments. In this role you will: - Lead the team to design and implement automation for model training, testing, validation, and deployment - Collaborate with machine learning engineers to ensure efficient deployment and scaling of ML models - Implement monitoring and alerting systems to track model performance, system health, and data drift - Optimize compute resources for cost and performance efficiency - Manage model versions to ensure traceability and reproducibility
• Design, develop, and deploy robust AI/ML systems with high-quality, scalable, and maintainable code • Translate complex, ambiguous requirements into clear technical plans and lead project execution across engineering efforts • Build scalable infrastructure and platforms to support cutting-edge machine learning workflows, including agentic systems that can plan, reason, and act autonomously • Research and apply state-of-the-art ML techniques—including LLMs, custom model training, and RAG/agent-based architectures—to real-world hardware challenges • Stay current with the fast-evolving AI/ML landscape, continuously improving our tools, systems, and methods to maintain a technical edge • Provide technical mentorship, foster a culture of excellence and inclusion, and help grow team capabilities • Lead design discussions, author technical documentation, and provide thoughtful, actionable feedback to peers • Represent the team in executive reviews, product demos, retrospectives, and cross-functional forums