Qualtrics is looking to hire a Machine Learning Engineering Manager for their AI Core organization to manage the entire model development lifecycle for AI/ML and Agentic applications. This role will focus on building and operating core reusable AI/ML components, including training pipelines, online model serving, feature stores, voice transcription, event stream processing, and LLM serving, to support billions of requests weekly and shape the future of Qualtrics' AI and model serving infrastructure.
Requirements
- Deep technical knowledge in building and operating AI/ML Platforms supporting the full model lifecycle, including orchestration.
- Experience building and shipping enterprise-grade AI solutions for global customers.
- Strong grasp of SRE and MLOps principles, expertise in system scalability, cloud cost optimization, AI observability, and production security.
- Experience programming in Java, C++, Python or related language
- Hands-on experience with real-time AI and Agentic services (e.g., Kubernetes, Sagemaker, Bedrock, Langgraph) and deploying GenAI applications, LLMs, or agent frameworks.
- Experience establishing and managing cloud infrastructure budgets (e.g., AWS, GCP, Azure) by designing for efficiency and scale.
- Experience with FedRAMP, ISO 42001, GDPR, PCI, HIPAA and other standards.
Responsibilities
- Define and gain alignment on a multi-quarter technical roadmap for one or more critical platform areas (e.g., LLM Serving or the Feature Store), demonstrating a clear plan for scalable, measurable impact.
- Run Team Operations with Structure and Empathy: Lead execution through consistent team rituals (planning, retrospectives, one-on-ones), balancing structure with empathy for alignment and psychological safety.
- Stay hands-on by participating in code reviews, technical design discussions, and occasionally contributing to the codebase.
- Instill best practices for software development and documentation, ensuring high-quality deliverables on time.
- Actively manage, mentor, and coach your team, fostering professional development and strong team culture.
- Work closely with global clients to provide solutions and ensure outstanding customer experiences.
- Recruit, hire, and develop top engineering talent to build a world-class team.
Other
- 10+ years of total experience in ML engineering, focusing on large-scale data, distributed systems, or ML infrastructure.
- 3+ years of direct people management, leading high-performing ML teams, building models for business application experience and development of senior/staff talent.
- Proven ability to build and lead engineering teams with strong product ownership and end-to-end accountability.
- Demonstrated success as an engineering manager, showing measurable outcomes like improved velocity, reduced cycle time, and scaling teams through high-growth AI apps.
- Successful track record leading complex, cross-functional initiatives across distributed teams, aligning engineering execution with product/business goals.
