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This role involves reviewing, negotiating commercial contracts, managing the NDA process, and advising stakeholders. The attorney will build contracting infrastructure and coordinate with outside counsel on legal matters.

Work with enterprise customers to identify high-value tabular ML use cases, design production-grade architectures, prototype solutions, lead deployments, coordinate cross-functional teams, and codify reusable deployment patterns to scale adoption of the NEXUS tabular foundation model.

Design, build, and operate cloud infrastructure and Kubernetes clusters for GPU/ML workloads; implement GitOps, IaC (Terraform), CI/CD, monitoring, automation (Python/Bash), and cost-optimization alongside ML engineers.

The Data Research Engineer will enhance ML model development by identifying data sources, building ETL pipelines, and collaborating on data storage solutions.

Own end-to-end SDLC and toolset standardization across Applied AI, Engineering, and Research. Formalize FDE-to-product handoffs, align APIs and technical specs, run cross-team operating rhythms, remove delivery blockers, and provide leadership with accurate forward capacity and delivery accountability.

Build and maintain Extensions backend for enterprise LTM products: design distributed, reproducible, observable workflows; optimize latency and throughput; collaborate with data scientists; drive architectural decisions; write high-quality, tested Python code; and document best practices for production-scale deployments.

Research, develop, and productize data-science methods to improve NEXUS predictive performance on enterprise tabular datasets. Implement production-quality Python components, design experiments and benchmarks, handle real-world tabular data challenges, collaborate with Research and Engineering, and validate approaches on customer datasets to drive product features.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Contribute to designing, implementing, and evaluating ML models, ensuring performance across the entire lifecycle while facilitating rapid development and testing of new ideas.

The Solutions Architect leads technical discovery, designs solutions, and guides enterprise customers through deploying predictive applications using a foundational AI model.