Virtue AI is looking to build the essential guardrails and red-teaming tools that enable organizations to deploy multi-modal AI applications confidently and responsibly
Requirements
- Strong backend and cloud engineering skills and experience building developer-facing libraries, APIs, or tools
- Strong product sense for internal platforms: you think in interfaces, reusability, and team velocity
- Experience building ML infrastructure or tooling for training, tuning, and inference workflows
- Comfortable working with systems like Sagemaker, Vertex AI, Kubernetes, Ray, or similar distributed compute environments
- Strong familiarity with the ML development lifecycle and tools like W&B, HuggingFace, MLFlow, DVC, or custom registries
- Proficiency in Python (strongly preferred) and cloud infrastructure
- Experience with containerized deployment patterns (e.g., Docker, Helm charts) and infrastructure abstraction
Responsibilities
- Develop SDKs, CLIs, APIs that expose platform capabilities (training & fine-tuning pipelines, inference stacks, feedback loops, quantization, and deployment) in a consistent, developer-friendly way across heterogeneous environments (e.g., Vertex AI, GKE, Together.ai)
- Design and build core components of our ML platform, including model registries, experiment tracking integrations (W&B), and cataloging systems for red-teaming, guardrails and agentic datasets and models
- Create tooling that supports reproducibility, version control, and benchmarking of models and datasets across internal R&D, on-prem and SaaS
- Build robust abstractions over infrastructure (e.g., Vertex AI, Ray, Kubernetes), enabling ML practitioners to run jobs and deploy models without needing to understand low-level infra
- Develop and maintain internal libraries that integrate with CI/CD, model tracking, QA, and security/compliance review workflows
- Implement lightweight and performant observability tooling across training and inference platforms (e.g., GPU utilization and performance (accuracy, latency, throughput) regressions)
- Help define the model packaging and deployment interfaces used across our on-prem (Helm, Docker, HuggingFace, Github Actions) and cloud environments
Other
- Collaborate with security and compliance stakeholders to ensure platform tools are secure, tenant-aware, and audit-ready
- Support internal onboarding and usability by contributing to platform documentation, quickstarts, and dev support workflows
- Virtue AI, Inc. is an Equal Opportunity Employer
- All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, breastfeeding, and related medical conditions), sexual orientation, gender identity or expression, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic or background protected by federal, state, or local law
- High-performing, motivated engineer ready to make a significant impact in the AI security space
