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 bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.
A career at Equinix means being at the center of shaping what comes next and amplifying customer value through innovation and impact. You’ll work across teams, influence key decisions, and help shape the path forward. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.
Job Summary
Designs, develops and manages the lifecycle of a product or group of products from concept to launch to end of life. Translates market opportunities and customer demand into viable products and services that differentiate Equinix in the market. Sets the vision and strategy for their product ensuring it is competitively positioned and customer-centric. Manages the product roadmap including features, upgrades and maintenance of the product or product line. Works cross functionally with user experience, engineering, operations, solution architects, marketing and others to design, build and launch new products and/or product features.
Responsibilities
Own model selection
Define how Equinix chooses models for each application. Criteria include task quality on our own evals, cost per task, latency, context length, tool-use ability, hardware footprint, license terms and data-handling requirements
Maintain a recommended-model catalogue across open-weight and proprietary models, with clear guidance on when each fits
Track new model releases, benchmark them against Equinix workloads, and decide when an upgrade is worth the switching cost
Lead model customization
Set the playbook for adapting models, from prompt and context engineering and retrieval to supervised fine-tuning, parameter-efficient methods (such as LoRA), preference optimization, reinforcement learning from feedback, distillation and quantization
Help teams choose the lightest technique that meets the bar. Prompting and retrieval come first, and training is used where it clearly pays off
Define the data strategy behind tuning, including curation, labeling, synthetic data generation, deduplication, and protecting against leakage between training and evaluation data
Build the platform
Own the roadmap for a shared model customization platform covering data preparation, training, evaluation, registry, deployment and lifecycle management
Partner with infrastructure and engineering teams on GPU capacity, training and serving stacks, inference optimization, and cost controls
Make tuned models reproducible and supportable, with versioned data, configs and checkpoints, clear ownership, and rollback
Partner with vertical teams to launch
Work with business and domain teams to scope use cases, pick models, design tuning experiments and launch to production
Turn early wins into repeatable patterns, templates and services that the next team can reuse
Run model launch reviews covering quality, safety, cost, performance and operational readiness
Measure and improve
Define the evaluations every model must pass before launch: task-specific quality, regression against the base model, safety, robustness and cost and latency targets
Partner with the Agent Intelligence team so tuned models are measured in production and feedback flows back into better data and better models
Report the impact of customization in terms leaders care about, such as quality gained, cost saved, latency reduced and risk avoided
Govern models responsibly
Set standards for license review, model provenance, data rights, model documentation, red-teaming and approval to deploy
Make sure confidential and customer data used in tuning is handled within Equinix’s security, privacy and regulatory requirements
Lead across the organization
Be Equinix’s go-to product leader on model selection…