Model Evaluation Engineer

Advance AI reasoning in physics

Validate and refine AI problem-solving capabilities

Benchmark and improve AI model capabilities

Design consulting-style prompts and evaluations

Improve security detection capabilities in GitLab

Enhance vulnerability research and analysis

Promote energy efficiency concepts and services to customers

Identify cost-effective investments in energy efficiency

Lead People Operations and HR functions effectively

Manage Total Rewards and compensation planning efficiently

Collaborate with various stakeholders on compensation issues

Lead benchmarking efforts to ensure competitive compensation levels

Analyze and advise on strategic partnership frameworks with global card networks.

Develop partner engagement models and contractual approaches.

Lead a team of Rust engineers for Sensor development

Ensure end-to-end delivery of Sensor features

Maintain compensation records and job data.

Support merit, bonus, and promotion cycles.

Lead outreach to building owners for BEPS support.

Provide energy and emissions reduction services.

Lead end-to-end model evaluation.

Develop benchmarking pipelines.

Design and optimize Starshield AI integrations.

Develop software for government use.

Support global compensation programs and annual cycles.

Conduct compensation analysis for pay equity and benchmarking.

Assist in data collection and cleaning for compensation analysis.

Support market research and external benchmarking of pay ranges.

Optimize large-scale models using advanced techniques.

Develop pipelines for model conversion and deployment.

Utilize AI tools for process improvements.

Ensure job architecture supports global expansion.

Model de novo protein generation.

Optimize protein designs with in-loop data.

Liaise with product team for insights.

Manage and coach a direct report.

Recruit native Spanish speakers from specified countries.

Create prompts for training AI models.

Upgrade Compensation and Benefits strategy.

Manage and maintain compensation ranges.

Port and enable benchmarks on new hardware.

Evaluate performance across various subsystems.

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.

Provide hands-on support for databases.

Diagnose and resolve production issues.

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.

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.