Machine Learning Engineer

Company Description Moveworks is an AI Assistant platform that helps leading global organizations empower their workforce with AI that gets work done. The company unifies siloed business applications across HR, IT, Finance, Procurement, and more into an intuitive, AI-native experience that supports employees in over 100 languages. Moveworks combines search and action in a single interface, provides hundreds of built-in integrations, and enables developers to deploy specialized AI agents for diverse business needs. Its advanced Reasoning Engine automates complex, multi-step processes reliably and efficiently, while robust security protocols and real-time governance ensure safe, compliant operation. Moveworks delivers measurable ROI for enterprises such as Toyota, Instacart, CVS Health, Marriott, HP, GitHub, Hearst, Databricks, and Micron.Role Description This is a full-time, on-site Machine Learning Engineer role based in Mountain View, CA. The Machine Learning Engineer will design, build, and optimize machine learning models and AI agents that power Moveworks’ core platform, with a focus on search, action, and reasoning capabilities. Day-to-day responsibilities include developing algorithms for pattern recognition, training and evaluating neural network architectures, performing data analysis and statistical modeling, and collaborating with product and engineering teams to ship scalable, production-grade systems. The role also involves improving model reliability, latency, and explainability, integrating models with existing services and APIs, and contributing to experimentation frameworks, tooling, and documentation. The Machine Learning Engineer will work closely with cross-functional partners to translate business requirements into technical solutions that enhance employee experiences and deliver measurable business impact.Qualifications Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable systems and data structures.Expertise in Pattern Recognition and Neural Networks for building models that understand and act on complex, real-world enterprise data.Applied knowledge of Statistics for experimentation, A/B testing, model evaluation, and data-driven decision-making.Proficiency in modern machine learning frameworks and languages (e.g., Python, PyTorch, TensorFlow) and experience deploying models to production.Experience working with large-scale data pipelines, cloud platforms, and microservices architectures.Strong problem-solving skills, clear communication, and ability to collaborate with cross-functional teams in a fast-paced environment.Bachelor’s degree or higher in Computer Science, Electrical Engineering, Mathematics, or a related technical field, or equivalent practical experience.Background in NLP, information retrieval, or conversational AI, and experience in enterprise or B2B SaaS environments are highly beneficial.