Customer Success Engineer

Manage and respond to system incidents.

Enhance monitoring and logging systems.

Architect alliances with hardware partners.

Identify decision-makers within partner organizations.

Implement and maintain cloud infrastructure with IaC.

Improve CI/CD pipelines for applications and ML workloads.

Evaluate models across accuracy and latency.

Build benchmarking pipelines for competitive analysis.

Support delivery of data center programs.

Manage timelines and project scope.

Conduct comprehensive model evaluations.

Establish and maintain benchmarking pipelines.

Oversee model evaluation across various metrics.

Build and maintain benchmarking pipelines.

Partner with engineering leaders for sourcing plans.

Lead sourcing across infrastructure and AI technology.

Unify technology strategy and enhance decision-making.

Oversee cross-functional initiatives from start to finish.

Develop and maintain ML platform infrastructure.

Provide shared components for deployment and API design.

Build automation tools for resource delivery.

Collaborate with engineering teams for quality product delivery.

Lead strategic partnerships with key industry players.

Develop go-to-market strategies for AI and GPU deployments.

Ensure user privacy across data handling.

Develop tools for privacy enhancement.

Lead security and infrastructure strategy.

Manage and develop security teams.

Conduct comprehensive model evaluations.

Develop and maintain benchmarking pipelines.

Lead end-to-end model evaluation processes.

Develop and maintain benchmarking pipelines.

Conduct comprehensive model evaluations.

Build and maintain benchmarking pipelines.

Lead end-to-end model evaluation.

Build competitive benchmarking pipelines.

Build and lead a team of Solutions Architects.

Align skills and engagement models to customer needs.

Lead end-to-end model evaluation.

Develop benchmarking pipelines.

Conduct comprehensive model evaluations.

Develop benchmarking pipelines for competitive analysis.

Conduct comprehensive model evaluations.

Build and maintain benchmarking pipelines.

Own and manage a named FS account list.

Drive net new ARR and expansion revenue.

Lead the technical direction for identity and engagement services.

Oversee mission-critical infrastructure related to identity and engagement.

Understand and assess enterprise customer needs.

Collaborate with various teams to manage accounts.

Develop a high-performance search and indexing ecosystem.

Contribute to open-source libraries for data processing.

Oversee model evaluation processes.

Build and maintain benchmarking pipelines.

Lead IT strategy to support company growth.

Build and manage an effective IT team.

Lead backend system improvements.

Make architectural decisions for reliability.

Drive revenue growth for GSI accounts.

Develop strategic insights for each firm.

Design and implement privacy-focused software.

Translate privacy policies into technical safeguards.

Own end-to-end model evaluation.

Build and maintain benchmarking pipelines.

Conduct end-to-end model evaluations.

Build competitive benchmarking pipelines.

Conduct end-to-end model evaluations.

Build and maintain benchmarking pipelines.

Understand customer business and data needs.

Collaborate effectively with various teams.

Understand Enterprise customer needs.

Collaborate with internal teams for account planning.

Understand enterprise customer needs and use cases.

Collaborate with multiple teams for solution development.

Conduct end-to-end model evaluations.

Build and maintain benchmarking pipelines.

Conduct end-to-end model evaluations.

Design and implement benchmarking pipelines.

Design and develop scalable platform infrastructure.

Anticipate and mitigate bottlenecks in workflows.

Conduct comprehensive model evaluations.

Build and maintain benchmarking pipelines.

Support server hardware and infrastructure.

Monitor and resolve issues via JIRA and communication channels.

Own end-to-end model evaluation.

Build and maintain benchmarking pipelines.

Own the end-to-end model evaluation process.

Build and maintain competitive benchmarking pipelines.

Contribute to Okta's FedRAMP initiative.

Design and develop cloud infrastructure.

Find and integrate new audio data sources.

Operate and extend cloud infrastructure.

Conduct end-to-end model evaluations across various metrics.

Build and maintain benchmarking pipelines.

Build an internal ML/AI platform.

Enable AI model fine-tuning.

Lead a global incident response team.

Oversee incidents from detection to resolution.

Conduct end-to-end model evaluations.

Build competitive benchmarking pipelines.