微软Senior Applied Scientist - CoreAI Voice Agent
任职要求
Required Qualifications: Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ 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 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research). Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications: • 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping. • Master's Degree in Statistics, Econometrics, Computer S…
工作职责
OverviewThe CoreAI Voice Agent team brings together talents in the areas of signal processing, speech modeling, statistical modeling and deep learning to develop and deliver robust, natural and scalable speech technologies, across a rich set of scenarios and languages. We welcome Applied Scientists to join our cutting-edge voice agent team. You’ll work at the intersection of deep learning, signal processing, and speech/audio modeling to push the boundaries of natural, expressive, and multilingual speech generation. Your innovations will power next-generation products in conversational AI and accessibility—impacting and enriching the lives of millions of users worldwide. 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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities• Design and develop novel speech algorithms to advance state-of-the-art technologies, with a focus on real-world applications in speech generation • Tackle scalability challenges by aligning solutions with evolving stakeholder requirements • Leverage large-scale computing frameworks, data analysis platforms, and modeling environments to enhance model performance and efficiency • Deploy models into production environments and iterate based on empirical results and user impact • Conduct rigorous experimentation by evaluating multiple models in live scenarios to assess comparative performance • Continuously monitor deployed algorithms to ensure they meet expected behavior, accuracy thresholds, and performance guardrails
• Ship features with PM & Engineering. Co‑own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets. • Model development & optimization. Design, fine‑tune, and evaluate models for LLM‑based authoring, summarization, reasoning, voice/chat, and personalization (e.g., SFT, alignment, prompt/tool use, safety filtering, multilingual & multimodal). • Data & evaluation at scale. Build/extend data pipelines for curation/labeling/feature stores; author offline eval harnesses; run online A/Bs and interleavings; define guardrails and success metrics; author scorecards and decision memos. • Production ML engineering. contribute to service code and configs; add monitoring, tracing, dashboards, and auto‑scaling; participate in on‑call and postmortems to improve live‑site reliability. • Responsible AI. Produce review artifacts, document mitigations for safety/privacy/fairness, support red‑teaming and sensitive‑use checks, and align with Microsoft’s Responsible AI Standard. • Collaboration & mentoring. Partner across PM/ENG/Design/CE/ORA/CELA; share methods and code, review PRs, improve reproducibility and documentation; mentor junior scientists.
• Apply state-of-the-art research and advanced algorithms to develop scalable, data-driven solutions that deliver measurable product impact. • Collaborate with product, engineering, and research teams to transfer technology and integrate innovative approaches into production systems. • Design and optimize machine learning models and data pipelines for large-scale applications, ensuring performance, scalability, and ethical standards. • Mentor and guide less experienced team members, fostering technical growth and sharing best practices across projects. • Stay current with industry trends and emerging technologies; publish research and share insights to advance innovation and business impact. • Incorporate fairness, bias detection, and privacy considerations into research and product development processes. • Drive improvements in data quality and leverage advanced analytics to identify opportunities for product enhancement.
• Design and implement offline evaluation strategies that capture real-world usage and reflect end-user preferences. • Develop scientifically sound metrics that diagnose model regressions, benchmark against baselines (e.g., ChatGPT, Glean), and validate product improvements. • Manufacture synthetic yet realistic user activity data using LLMs to simulate diverse usage scenarios. • Collaborate on multi-agent systems or agentic workflows to automate evaluation flows and generate high-signal insights. • Analyze evaluation outputs to identify gaps in coverage, quality, and usability across Copilot canvases. • Partner with engineering and PMs to ensure insights are integrated into product workflows and experimentation pipelines. • Publish learnings in internal forums, external conferences, and contribute to best practices in applied science.
• Drives product impact by transferring cutting-edge research into production systems. Collaborates across Microsoft and external groups to apply scalable, data-driven solutions, author white papers, file patents, and consult on product strategy. • Designs and optimizes ranking algorithms across L1–L3 stages using collaborative filtering, deep neural networks (DNN), and graph neural networks (GNN). Applies FastRank and LambdaMart techniques for precision ranking in Bing Feeds and other verticals. • Leads experimentation and deployment of large-scale NLP and LLM models for topic modeling, sentiment analysis, and multimodal content linking. Supports real-time indexing and modular APIs for rapid model onboarding. • Cleans, transforms, and analyzes large-scale data to build usable datasets and optimize feature selection. Develops ETL pipelines and mentors teams in data preparation and signal system design. • Operates on distributed GPU/CPU frameworks (DLTS, DeepSpeed) for training and inference. Supports A/B testing, flighting, and real-time feedback loops to refine models and improve user engagement. • Applies deep understanding of fairness and bias in model development. Contributes to internal ethics policies and ensures representative data usage aligned with responsible AI principles. • Coaches junior team members, collaborates with academia to recruit top talent, and shares research findings through publications and conferences. Builds multidisciplinary teams and fosters innovation culture.