SandboxAQ is seeking to mature its MLOps practices to deliver AI solutions that address some of the world's greatest challenges, including advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
Requirements
- 7+ years of experience with MLOps fundamentals: automated training, evaluation, and retraining loops, dataset and model versioning tools, systems for serving inference, build end-to-end ML pipeline using industry-standard tools.
- Deep experience with at least one major cloud provider. GCP preferred.
- Experience with managing complex data governance requirements.
- Familiarity with MLOps architectures and best practices for LLMs and Agentic systems.
- 3+ years of experience with infrastructure as code management of public cloud providers. Familiar with terraform. GCP preferred.
- Familiarity with building and maintaining CI/CD pipelines for ML systems.
- 3+ years of experience with Python, with strong knowledge of software design principles.
Responsibilities
- Mature our MLOps practice by defining processes and building fundamental tooling.
- Embed closely with R&D teams to assist in delivering project goals and drive adoption of practices and tooling.
- Drive the design and implementation of complex, security-sensitive data processing and storage systems with complex tenancy and data isolation requirements.
- Collaborate closely with the product team and internal stakeholders in all phases of software development to validate the solutions you propose and implement.
- In collaboration with the rest of the engineering team, build and manage infrastructure for SandboxAQ’s simulation and data platform.
- Review code and participate in design and architectural discussions.
Other
- Excellent communication and collaboration skills, with the ability to effectively influence a cross-functional team.
- 7+ years of experience
- 3+ years of experience
- Ability to work in a fast-moving software development team
- Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
