Machine Learning Engineer

Overview In this role you will advance autonomous AI agents that proactively assist users and automate complex talent workflows. You’ll work on scalable agentic systems that impact millions of users, partnering with product, UX, and engineering to deliver intelligent experiences. You will leverage the latest AI advances to improve agent autonomy and integration with enterprise data. This is a hands-on, impact-driven opportunity to shape agentic talent systems at scale. Compensation / Benefitshybrid work modelequity (pre-IPO stock options)discretionary bonuscompetitive base salaryfamily medical vision and dental coverageEEO commitment ResponsibilitiesResearch, design, and deploy advanced AI agents and agentic systemsArchitect multi-agent frameworks including planning and executionIntegrate LLMs and state-of-the-art AI techniques to boost agent intelligenceBuild scalable infrastructure to support agent deployment at scaleCollaborate with product managers, UX designers, and engineers to define requirementsDiagnose and optimize performance in distributed environmentsContribute to team knowledge sharing and keep abreast of AI advancementsLeverage enterprise and user data to craft personalized agent experiencesContribute to Copilot GenAI Workflows for Users for chat-like command execution Key requirementsKnowledge and passion for machine learning, Gen AI, LLMs, and NLPUnderstanding of agent-based modeling, reinforcement learning, and autonomous systemsExperience with LLMs and applications in Agentic AIProficiency in Python; experience with TensorFlow or PyTorchExperience with AWS and containerization (Docker, Kubernetes)Understanding of distributed design patterns and microservicesStrong coding and algorithms skillsExcellent problem-solving and data analysis abilitiesStrong communication and collaboration skillsMaster in Computer Science, AI, or related field, or equivalent experienceMin 1-3+ years of relevant ML work experiencecollaborationcommunicationproblem-solvingPythonTensorFlowPyTorch