United States onlyWe are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'—an AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.
Responsibilities
- Architect, build, and operate end-to-end ML pipelines for training, validation and deployment on Google Cloud.
- Define, instrument, and maintain logging, monitoring, and alerting for model performance and data drift.
- Automate CI/CD for ML artifacts and infrastructure using GitHub Actions or equivalent.
- Collaborate with cross-functional teams, including frontend engineers, backend engineers, research engineers, and infrastructure engineers.
- Write clean, well-documented, fast, and maintainable code.
- Help ensure our systems have high availability and performance.
What we're looking for
- BS in Computer Science or a related field.
- 5+ years of experience as a AI/ML Ops, DevOps, Infrastructure Engineer or equivalent.
- Expert-level Python and TypeScripts skills.
- Experience with Docker, Kubernetes, Terraform, and Google Cloud.
- Deep understanding of large language models (LLMs) and prompt-engineering best practices.
- Experience designing and maintaining CI/CD pipelines to fine-tune or train LLM models.
- Excellent written and verbal communication skills.
Bonus Points
- Experience in computer graphics or physics-based simulation.
- Background in setting up Prometheus/Grafana, ELK, or similar monitoring stacks.
- Experience with Vertex AI.
- Experience working with custom Domain-Specific Languages.
