Director, Machine Learning

Overview

Who are we?

Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.

A place where tech thinkers and future builders turn bold ideas into breakthrough experiences. We welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

The Director of Machine Learning is a senior leadership role responsible for shaping, executing, and scaling the organization’s machine learning strategy. This leader oversees the development and deployment of advanced ML models, guides cross-functional teams, and ensures the organization leverages AI technologies to drive innovation, efficiency, and business impact. The ideal candidate has deep technical expertise, proven leadership experience, and the ability to translate complex ML concepts into meaningful business outcomes.

• Strategic Leadership

• Develop and own the company-wide machine learning strategy aligned with business objectives

• Identify high-impact opportunities for ML across products, operations, and customer experiences

• Advocate for ethical, secure, and responsible AI development and usage

• Team & Project Management

• Lead, mentor, and grow high-performing teams of ML engineers, data scientists, and research scientists

• Establish best practices in model development, experimentation, deployment, and monitoring

• Allocate team resources and prioritize projects to balance innovation with ROI

• Technical Leadership

• Oversee the design, development, and deployment of production-grade machine learning models

• Partner with engineering leadership to build scalable ML infrastructure, including MLOps, data pipelines, and cloud architecture

• Review and guide technical work, ensuring scientific rigor, reproducibility, and quality

• Cross‑Functional Collaboration

• Work closely with product, engineering, data, and executive teams to align ML initiatives with organizational goals

• Communicate complex ML concepts—tradeoffs, risks, timelines—to non-technical stakeholders

• Support product strategy by integrating ML capabilities into roadmaps

• Governance & Performance

• Implement processes for model governance, bias monitoring, versioning, and auditability

• Track and report on key ML KPIs, model performance, and business impact

• Ensure compliance with regulatory standards related to AI/ML as applicable

Required

• Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or related field

• 10+ years of experience in ML/AI engineering, data science, or applied research

• 5+ years leading technical teams, including people management responsibility

• Expertise in modern ML techniques (deep learning, LLMs, reinforcement learning, generative models, etc.)

• Proficiency with ML frameworks and tools (e.g., Tensor Flow, PyTorch, Scikit-learn, Hugging Face)

• Strong understanding of MLOps, cloud platforms (Azure, AWS, GCP), and scalable data architectures

• Proven track record deploying ML models into production environments

Preferred

• Experience building ML platforms or ML-driven products at scale

• Background working in regulated industries (finance, healthcare, etc.) if relevant

• Demonstrated experience with LLM fine-tuning, retrieval-augmented generation (RAG), or generative AI

• Strong business acumen and ability to influence senior leaders

• Strategic thinking and vision‑setting

• Excellent communication and stakeholder management

• Technical depth paired with practical delivery

• Leadership, coaching, and talent development

• Innovation mindset with data‑driven decision-making

The targeted pay range for this position in the following location is / locations are:

United States - Redwood City Office GHQ : 240, USD / Annual

Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.
The pay range shown is based on our compensation structure in place at the time of…