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Equinix

Director, AI Engineering

RemoteUnited States only
Published
Role
Fullstack
Experience
Senior
Employment
Full-time
$269k–$403k/yr
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Open to US only. Set where you work from to check your eligibility.

No BS summary

We are seeking a Director of AI Engineering to lead and scale a high-performing Machine Learning Engineering (MLE) organization. This leader will be responsible for building production-grade AI/ML systems that power next-generation generative and predictive capabilities across the enterprise.

Core skills

TensorFlow/PyTorchMLOps

Required skills

cloud-native architecturesLLMs/RAG/prompt engineeringdistributed systems/APIs/microservices architecture

Optional skills

enterprise AI platformsinternal AI productspredictive MLgenerative AIglobal delivery models

Required languages

English unknown

What you'll do

  • Build, lead, and mentor a global team of Machine Learning Engineers and technical leaders
  • Establish a high-performance engineering culture focused on quality, velocity, and accountability
  • Drive hiring, onboarding, and career development for MLE talent across regions
  • Own end-to-end delivery of ML platforms, pipelines, and services (training, inference, monitoring)
  • Operationalize models into scalable, reliable, and secure production systems
  • Partner with Data Science and Product to move from experimentation to deployment
  • Set the vision for ML platform architecture, MLOps, and GenAI enablement
  • Standardize tools, frameworks, and best practices for model development and deployment
  • Ensure systems are built for scale, performance, and cost efficiency
  • Lead development of GenAI capabilities (LLMs, RAG, copilots, automation workflows)
  • Enable reusable AI services and APIs to accelerate use case delivery
  • Stay ahead of industry trends and translate them into enterprise-ready capabilities
  • Partner with Product, Data, Engineering, and Business leaders to prioritize high-impact use cases
  • Communicate strategy, progress, and outcomes to executive stakeholders
  • Align AI initiatives with business goals, including revenue growth, efficiency, and customer experience
  • Establish best practices for model governance, monitoring, and lifecycle management
  • Ensure compliance with security, privacy, and ethical AI standards
  • Implement guardrails for safe and responsible use of AI technologies

What they require

  • 12+ years in software engineering, data engineering, or ML engineering
  • 5+ years leading large, distributed engineering teams (including managers of managers)
  • Proven track record of delivering ML/AI systems at scale in production environments
  • Deep knowledge of machine learning systems, MLOps, and cloud-native architectures
  • Experience with ML frameworks (e.g., TensorFlow, PyTorch) and data platforms
  • Strong understanding of GenAI/LLMs, prompt engineering, and retrieval-augmented systems
  • Familiarity with distributed systems, APIs, and microservices architecture
  • Strong ability to translate business strategy into technical execution
  • Experience driving large-scale transformation initiatives
  • Excellent communication and stakeholder management skills

Benefits

  • Employee Assistance Program
  • Insurance: health, life, disability and voluntary plans
  • Retirement plan with Equinix contributions
  • Paid Time Off (PTO) and Paid Holidays

data center and colocation infrastructure provider

🇺🇸 United StatesDigital InfrastructureEnterpriseequinix.com
$269k–$403k/yr