NewSenior Researcher - AI Agents - Microsoft Research MicrosoftSenior Researcher - AI Agents - Microsoft ResearchRedmond, WA$119,800–$234,700 / yearRelevant projects from our lab include agentic systems (e.g., Magentic-UI , Magentic-One ), ecosystems (e.g., Magentic Marketplace ), frameworks (e.g., AutoGen ), models (e.g., Phi , Orca ) and tools (e.g., AgentInstruct , AutoGen Studio ). We regularly release open-source models, libraries, and tools to accelerate community progress, while also working within Microsoft’s ecosystem to ship AI technologies across multiple products, ensuring our innovations create real-world value for people.
NewPrincipal Software Engineer, Foundry Agents - CoreAI MicrosoftPrincipal Software Engineer, Foundry Agents - CoreAIRedmond, WA$142,800–$274,800 / yearWithin CoreAI, the Foundry Agents organization is responsible for key ownership areas across the end‑to‑end agent lifecycle: (a) Foundry Agents platform to deploy and run agents securely at enterprise scale with seamless integration with governed tools, (b) model fine‑tuning to train and improve agentic performance, and (c) Foundry observability to generate insights from agentic traces and continuously evaluate and optimize agents. Masters Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelors Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
NewSenior Product Manager, Agent 365 Tools MicrosoftSenior Product Manager, Agent 365 ToolsRedmond, WA$119,800–$234,700 / yearAs organizations connect agents to a fast-growing ecosystem of MCP (Model Context Protocol) servers, plugins, skills, connectors, and custom integrations, the ability to onboard, discover, and govern those tools becomes essential to enterprise trust. We are looking for a Senior Product Manager to own the tool governance experience in Agent 365, the product that lets customers inventory, register tools, discover unsanctioned ones, and apply consistent policy and controls across them.
NewPrincipal Product Manager - AI Security (CoreAI) MicrosoftPrincipal Product Manager - AI Security (CoreAI)Redmond, WA$142,800–$274,800 / yearThere is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year. This includes integrating AI security capabilities with Microsoft’s broader security stack - including Microsoft Defender, Entra, Purview, and Azure AI Foundry - to deliver a comprehensive security platform for AI systems.
NewPrincipal Software Engineer MicrosoftPrincipal Software EngineerRedmond, WA$142,800–$274,800 / yearOwning the architecture and run-state reliability of AI-driven support workflows; defining the reliability bar for incident response and live-site health; and serving as a designated responsible individual (DRI) who leads incident retrospectives to identify root causes, owns repair actions, and prevents recurrence across the platform. Industry or company-wide thought leadership in AI engineering—for example, driving adoption of emerging technologies, representing engineering to executives and external audiences, or contributions such as patents, publications, or widely adopted internal frameworks.
NewProduct Strategy Lead - Revenue Forecast Modeling Salesforce.com, Inc.Product Strategy Lead - Revenue Forecast ModelingSeattle, WA$123,100–$186,300 / yearBuild executive-ready deliverables including decision memos, leadership briefings, board-level decks, strategy narratives, business cases, and forecast/commit reporting that simplify complexity without losing rigor. Responsibilities: Own business use case revenue forecast modeling - build and maintain the analytical models that translate initiative drivers, pipeline, and consumption data into revenue forecasts and commit views for senior leadership to inform investment decisions.
Principal Machine Learning Engineer, Conversational AI Modeling and Learning Amazon.com IncPrincipal Machine Learning Engineer, Conversational AI Modeling and LearningBellevue, WAYou will own the architecture that turns research into production capability: large-scale agentic evaluation infrastructure (sandboxed, reproducible, statistically trustworthy at high concurrency), reinforcement learning training systems for long-horizon multi-turn trajectories, self-learning pipelines that convert production experience into permanent model and system improvements, and the serving architecture for latency-sensitive agentic inference. You will build the harnesses and sandboxed worlds agents act in, the evaluation systems that make their quality provable rather than asserted, the RL infrastructure that trains models on the same tasks they are measured on, and the self-improvement loop that turns every production interaction into a permanently smarter system - agents that ship better than they launched, week over week.
Staff Machine Learning Engineer (Modeling), Support BlockStaff Machine Learning Engineer (Modeling), SupportSeattle, WashingtonZone A: $276,800—$415,200 USD Zone B: $276,800—$415,200 USD Zone C: $276,800—$415,200 USD Zone D: $276,800—$415,200 USD Demonstrated leadership capabilities, with the ability to influence and align cross-functional teams while directly shaping the work of peers through communication, context sharing, and technical guidance.
Senior Machine Learning Engineer Active Secret Clearance Striveworks IncSenior Machine Learning Engineer Active Secret ClearanceTacoma, WA$185,000–$230,000 / yearSince 2018, we have delivered the most trusted AI systems operating in real-world use cases-providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab. Working directly with customers, data scientists, software engineers, and DevOps engineers, you'll define requirements and orchestrate complex data engineering pipelines.
Senior Machine Learning Engineer, Alexa-Conv A Modeling&Learning Amazon.com IncSenior Machine Learning Engineer, Alexa-Conv A Modeling&LearningBellevue, WAAlexa AI is building the next generation of Alexa+, Amazon"s LLM-powered conversational assistant, and its future is agentic: LLM systems that reason and act over dozens of chained inferences, coupled to real environments where their actions persist. Design, build, and operate major components of the agentic AI platform: evaluation harnesses, sandboxed environments, RL and post-training pipelines, self-learning data pipelines, or inference serving for agentic traffic.
Member of Technical Staff - Imagine Model SpaceXAIMember of Technical Staff - Imagine ModelSeattle, WA$180,000–$440,000 / yearDomain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video). ABOUT THE ROLE: As a multimodal engineer on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content (e.g., synchronized audio for video).
Research Scientist - Model Capability Boundary Exploration and AI Data Flywheel System Development - Global Frontier Tech Recruitment Program - 2027 Start (PhD) Beijing ByteDance Technology Co LtdResearch Scientist - Model Capability Boundary Exploration and AI Data Flywheel System Development - Global Frontier Tech Recruitment Program - 2027 Start (PhD)Seattle, WABeyond model serving, we operate large-scale log analytics pipelines that process massive volumes of invocation logs from text models, multimodal models, and agent systems - extracting usage patterns, quality signals, and actionable insights to inform model improvement, system optimization, and product decisions through continuous, data-driven feedback loops. Team Introduction: The Applied Machine Learning Enterprise team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platforms that offer businesses Model-as-a-Service (MaaS) solutions, serving both large model providers and downstream users.
Product Operations Manager, Model Quality Meta Platforms IncProduct Operations Manager, Model QualitySeattle, WAEvals owners own execution of verification pipelines within their products; this role ensures consistency and identifies gaps across the portfolio while building institutional competence by surfacing performance patterns and proven methodologies, enabling evals captains' ability to execute and unblocking them as needed Defines what leadership needs to see, how model health should be measured and reported, and what thresholds trigger escalation Provides thought partnership to evals managers on narrative of model health, provides visibility into our classification strategy and accuracy measurement process Works with evaluation managers to drive cross-app taxonomy alignment in alignment with cross-functional needs and advises on a strategy for the migration of LLM accuracy assessment to judges Owns the consolidated view of all production model performance, identifies systemic patterns and emerging risks, and ensures leadership can verify model health on demand Partners with AI Implementations, operational systems teams and the Metrics & Measurement team to build and maintain the infrastructure that surfaces this information Establishes performance guardrails that evals captains implement. Continuously scans industry developments and best practices to incorporate into org-wide approach Maintains a tight feedback loop with product and eng teams across apps to ensure alignment on production priorities and deployment risks Deploys deep SME expertise to diagnose, unblock and directly resolve technical bottlenecks to complex model quality problems (atrophy, accuracy regressions, performance plateaus) when evaluation leads encounter blockers they cannot resolve independently Drives alignment with cross-functional teams (quality and reliability partner teams) on tooling needs to support Product Operations classification strategy (ML classification tooling for initial-tier classification, user voice, breakdown graphs).
AIML - Site Lead & Lead Researcher, Foundation Models Apple IncAIML - Site Lead & Lead Researcher, Foundation ModelsSeattle, WAWere solving frontier problems in reward modeling to resist reward hacking, handling sparse and delayed rewards in agentic settings, and aligning models reliably across the spectrum from open-ended creative tasks to precise, action-taking workflows. Foster collaboration across teams and stakeholder groups, bridging research, product engineering, and business objectives to ensure breakthrough ideas reach millions of users.
Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) - AIGC Risk Intelligence TikTok IncTech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) - AIGC Risk IntelligenceSeattle, WAWe are transitioning from monolithic LLM applications to a structured multi-agent architecture that emphasizes: Tool-augmented reasoning (ReAct-style systems) Modular skill composition Execution traceability and observability Feedback-driven system evolution Cross-domain risk reasoning We are seeking an experienced technical leader to define and implement this architecture. Develop Open Risk Detection Capabilities Architect systems capable of identifying previously unseen risk patterns Implement execution trace-driven optimization loops Translate feedback signals (FP/FN, reviewer overrides, drift signals) into system improvements Enable proactive rather than purely reactive detection systems.
NewMachine Learning Engineer Graduate (E-Commerce Content Recommendation - Generative & Large Recommendation Model) - 2027 Start (PhD) TikTok IncMachine Learning Engineer Graduate (E-Commerce Content Recommendation - Generative & Large Recommendation Model) - 2027 Start (PhD)Seattle, WAReframe retrieval as generation: tokenize the item space into semantic IDs (RQ-VAE / SID) and train autoregressive models, grounded in MLLM semantics, to generate what a user wants next - collapsing the traditional "multi-channel retrieval + ranking" funnel into a single generative stage. Use large models real-world knowledge to mine latent user interests and semantic representations beyond what pure ID co-occurrence can express; use reasoning models to run explicit chain-of-thought inference over long-horizon user intent, making the system materially better at discovery and novelty.
NewEngineer, AI Agent Risk & Remediation TekWissen LLCEngineer, AI Agent Risk & RemediationSeattle, WA$61.52Our client provider of digital technology and transformation, information technology and services Position: Engineer, AI - Agent Risk & Remediation Location: Seattle, WA Duration: 6 Months Job Type: Temporary Assignment Work Type: Onsite Job Description: This role builds and runs the program that keeps every agent in the enterprise safe and current - not just the agents your team builds, but every agent built by every team across the company. As the agent population grows, you'll build the crawling agents that scan the whole fleet, spot what needs attention - agents on deprecating models, agents burning too many tokens, agents drifting out of policy - and tier the risk.
Software Engineering Manager, Ads Brand Measurement Audience Models Google LLCSoftware Engineering Manager, Ads Brand Measurement Audience ModelsKirkland, WATeams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
NewEngineer, AI — Agent Risk & Remediation Sumeru SolutionsEngineer, AI — Agent Risk & RemediationBellevue, WABuild the crawling agents that scan every agent in the enterprise - built by any team - for those needing attention: deprecating models, token overruns, policy drift, updates due. Route what can't be auto-fixed to each agent's owner and follow up to closure against SLA; SRE is one such owner, for the agents your team builds.
Applied Scientist - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Recruitment Program - 2027 Start (PhD) TikTok IncApplied Scientist - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)Seattle, WAProject Overview, Challenges & Value With the rapid development of AIGC and the globalization of content ecosystems, content moderation faces three major challenges: evolving policies, surging complexity in multilingual and multimodal content, and upgraded generative adversarial attacks. RL-driven agentic decision-making: end-to-end training of agent multi-step reasoning and tool-call strategies based on GRPO/PPO, overcoming bottlenecks in sample efficiency and training stability.