[Skip to main content](#main-content) [ OpenNash ](https://opennash.com/) / [Jobs](https://jobs.opennash.com/) [ 01 Search jobs](https://jobs.opennash.com/search/)[ 02 Companies](https://jobs.opennash.com/explore/)[ 03 Hiring report](https://jobs.opennash.com/reports/hiring/)[ 04 AI assistants](https://jobs.opennash.com/connect/)[ 05 How it works](https://jobs.opennash.com/methodology/) Microsoft # Senior Applied Scientist-Ads Monetization United States, Washington, Redmond, California, Mountain View Senior individual contributor Research & Science Listed on Microsoft’s official careers site. Posted October 21, 2026. Check that it is still open and apply there. [Apply on Microsoft’s careers site →](https://apply.careers.microsoft.com/careers/job/1970393556949556) [OpenNash Jobs](https://jobs.opennash.com/) / [Microsoft](https://jobs.opennash.com/companies/microsoft/) / Senior Applied Scientist-Ads Monetization ## Job description Work on large-scale machine learning challenges spanning user understanding, ad representation, retrieval, recommendation, ranking, and optimization, with the goal of maximizing value for both users and advertiser Apply and advance technologies in natural language processing (NLP), computer vision (CV), large language models (LLMs), Generative AI, and Agentic AI. Defining the ad relevance problem across different ad scenarios to optimize both the user and advertiser experience. Driving algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including the latest LLM models. Deploying robust and scalable solutions to continuously improve ad relevance. Analyzing model and system performance to identify opportunities based on offline and online testing. 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) 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 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 4+ years of experience developing natural language processing or multimodal machine learning systems using deep learning, including hands-on experience with transformer-based small language models (SLMs) or large language models (LLMs). OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers. 4+ years of experience developing and operating production machine learning or AI systems using Python, C++, or equivalent programming languages. Experience in online advertising. Experience with distributed training or inference for SLMs and LLMs, including data and model parallelism, mixed-precision training, checkpointing, experiment management, performance optimization, and efficient serving. Ability to work independently in a team to deliver innovative solutions solving challenging business/technical problems from high level vision and architecture, down to quality design and implementation. Experience evaluating SLMs, LLMs, or agentic systems using task-specific offline metrics, human or model-assisted evaluation, safety and robustness testing, latency and cost analysis, and controlled online experiments. Experience designing and implementing agentic AI systems that use tool calling, retrieval, planning, memory, structured outputs, multi-step workflows, or multi-agent coordination, with appropriate safeguards and observability. Experience applying responsible AI practices to model and agent development, including evaluation for safety, reliability, privacy, security, bias, groundedness, and misuse risks. Have publications at peer-reviewed Data Science/AI conferences (e.g. KDD- Knowledge Discovery and Data Mining, CIKM- Conference on Information and Knowledge Management, SIGIR- Special Interest Group on Information Retrieval, NeurIPS- Neural Information Processing Systems, CVPR- Computer Vision and Pattern Recognition, ICML International Conference on Machine Learning, ICLR- International Conference on Learning Representations, ICCV- International Conference on Computer Vision, and ACL- Association for Computational Linguistics). ## At a glance - Posted by the employer: Oct 21, 2026 - First seen by OpenNash: Aug 21, 2026 - Last checked: Nov 1, 2026 - Listed for: 72 days - Location: United States, Washington, Redmond, California, Mountain View[Apply on Microsoft’s careers site →](https://apply.careers.microsoft.com/careers/job/1970393556949556) ## Hiring at Microsoft - Open jobs: 2,199 - New in the last 7 days: After two weekly collections - Tracked since: Jul 10, 2026 [All Microsoft jobs](https://jobs.opennash.com/companies/microsoft/) · [Weekly hiring report](/reports/hiring/) ## More jobs at Microsoft ### [Principal Applied Scientist](https://jobs.opennash.com/companies/microsoft/jobs/ef278e5a1d551d877eb2/) United States, Washington, Redmond, California, Mountain View ### [Principal Applied Scientist - Copilot Quality](https://jobs.opennash.com/companies/microsoft/jobs/60fe2d307c1cda9f4d17/) United States, Washington, Redmond, California, Mountain View ### [Principal Applied Scientist-Ads Monetization](https://jobs.opennash.com/companies/microsoft/jobs/1ed023bd5f77158ca20e/) United States, Washington, Redmond, California, Mountain View ## Similar jobs at other companies ### [Senior Applied Scientist](https://jobs.opennash.com/companies/oracle/jobs/f8ed9ff14b05042cc65f/) Oracle · United States ### [Sr. Applied Scientist, Amazon Ads](https://jobs.opennash.com/companies/amazon/jobs/b72d747ce41f237be499/) Amazon · US, WA, Seattle ### [Senior Applied Scientist, PV Ads Science](https://jobs.opennash.com/companies/amazon/jobs/9d29bdbaf37d982b4ae8/) Amazon · US, WA, Seattle ### [Sr Applied Data Scientist - Search and Browse (applied ML, LLMs, ML Ops)](https://jobs.opennash.com/companies/target/jobs/0923ac6213001fd36d99/) Target · Canada ### [Senior AI/ML Applied Scientist](https://jobs.opennash.com/companies/unitedhealth-group/jobs/78af7d0e20840c30720f/) UnitedHealth Group · Eden Prairie, Minnesota OpenNash lists jobs from employers’ own careers sites and does not handle applications. Dates come from the employer where stated; “first seen” and “last checked” are our own observations. [ OpenNash ](https://opennash.com/) AI-native services firm that builds custom software and 24/7 AI agents. OpenNash Jobs is an OpenNash Applied AI project. [Book time with OpenNash](https://calendly.com/opennash/new-meeting?hide_gdpr_banner=1) Jobs - [Search jobs](https://jobs.opennash.com/search/) - [Companies](https://jobs.opennash.com/explore/) - [Hiring report](https://jobs.opennash.com/reports/hiring/) - [AI assistants](https://jobs.opennash.com/connect/) - [How it works](https://jobs.opennash.com/methodology/) OpenNash - [opennash.com](https://opennash.com/) - [Services](https://opennash.com/ai-agent-consulting/) - [OpenNash CX](https://opennash.com/cx/) - [AI Tools](https://opennash.com/ai-tools/) - [Blog](https://opennash.com/blog/) - [About](https://opennash.com/about/) Contact - [hello@opennash.com](mailto:hello@opennash.com) - [LinkedIn](https://www.linkedin.com/company/opennash) - [Support](https://jobs.opennash.com/support/) - [Privacy](https://jobs.opennash.com/privacy/) - [Terms](https://jobs.opennash.com/terms/) © 2026 OpenNash, Inc. Company names and public job postings belong to their respective owners. Employers control source availability and application decisions.