Top Tech Jobs & Startup Jobs

Technical lead for AI-driven relevance, recommendation, personalization, and agentic commerce. Drive ML research to production: model architecture, training, evaluation, experimentation, and scalable deployment. Partner with engineering and product teams, mentor scientists, and measure business impact across search, shopping, Copilot, and ads.

Lead IP selection, acquisition, release management, and integration for AI SoC programs. Establish scalable IP release/QA processes, track third-party and internal IPs, drive pre/post-silicon issue resolution, and partner with architecture, physical design, DFT, validation, packaging, and board teams to ensure high-quality IP delivery and successful product outcomes.

Lead product strategy and roadmaps for multimedia search experiences using qualitative and quantitative research, experimentation, and cross‑functional partnership. Drive product improvements in relevance, data, UX, and measurement, manage dependencies and partner plans, and present roadmaps and results to stakeholders and executive leadership.

Lead and grow an applied science team building text, image, and multimodal creative AI. Define science roadmap, drive LLM/multimodal innovation, partner cross-functionally to deliver scalable ad-facing solutions, establish metrics and experiments, and communicate strategy and impact to senior leadership to improve advertiser ROI and user engagement.

Define and lead product strategy for AI-native personalization platform across recommendations, user/content understanding, agentic memory, and generative content. Translate AI/ML capabilities into product requirements, build evaluation and experimentation frameworks, partner cross-functionally to move research to scalable systems, and balance relevance, safety, latency, cost, and long-term user value.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Define and drive product vision, strategy, roadmap, and execution for security and identity products. Collaborate with engineering, design, research, and data teams; engage customers; translate needs into requirements; prioritize features; define success metrics; support go-to-market; and monitor product performance to deliver enterprise-scale security solutions.

Design and implement native Windows components in modern C++; work on device redirection, input, display, audio/video, USB/HID and driver-adjacent code; diagnose kernel/user-mode issues, optimize performance and memory, and own features end-to-end including telemetry, dumps, and live-site debugging.

Build and operate secure production access services: design, implement, debug, and scale cloud-distributed systems. Own end-to-end features, drive release and validation practices, monitor live sites, respond to incidents, and collaborate cross-functionally to improve reliability, observability, and performance for internal customers.

Individual contributor software engineering role (IC4) at Microsoft. Posting lists U.S. base pay ranges (with higher SF/NYC ranges). Responsibilities and specific technical requirements are not included in the description.