As a Senior Machine Learning Engineer in AI Enablement, you will play a key role in advancing how product teams develop and deploy AI-driven features. Rather than building models directly, you'll focus on enabling others by sharing deep technical expertise and shaping scalable practices across the ML stack.
What You'll Do
- Advise product teams on solutions across core ML domains such as data pipelines, model evaluation, training workflows, inference optimization, and deployment infrastructure
- Collaborate closely with engineering and research partners to troubleshoot complex systems and identify efficient, sustainable paths forward
- Develop standardized patterns and best practices that streamline implementation and reduce duplication across teams
- Diagnose root causes of technical issues and disseminate insights to improve organizational knowledge
- Balance immediate problem-solving with long-term strategies to scale the impact of enablement efforts
What We're Looking For
- Proven experience in Python and common ML frameworks
- Familiarity with Kubernetes and distributed systems
- Hands-on background in building and debugging data pipelines and serving infrastructure
- Solid understanding of model evaluation methodologies and inference optimization techniques
- Strong communication skills with the ability to translate technical details for diverse audiences
- A collaborative approach focused on lifting the capabilities of others
- Ability to manage multiple initiatives simultaneously in a fast-paced environment
Environment and Impact
You'll work in a high-velocity setting where technical rigor meets practical execution. The culture emphasizes empowering peers, connecting research innovation with production systems, and delivering meaningful value to users through rapid iteration. Your work will directly influence how effectively teams across the organization adopt and implement AI technologies.
