What are the responsibilities and job description for the MLOps Engineer - Leading AI Firm - Up to $300K Base position at Saragossa?
Ever wanted to deploy ML models trained on massive physics simulations? Now’s your chance.
You would be coming on as a MLOps Engineer at a leading AI company, where large-scale simulation meets machine learning. Backed by a high-profile VC, their cloud-native platform runs thousands of high-fidelity simulations that fuel ML models across industries from energy to manufacturing.
In this role, you’ll own the infrastructure that takes models from research into production at scale. You’ll design and maintain end-to-end pipelines, deploy and monitor models in production, and ensure reliability across massive datasets, including complex 3D simulation data. You’ll need to be experienced with GCP, Kubernetes, Docker, Vertex AI, and modern MLOps frameworks like Kubeflow and MLflow.
This is a hands-on position where you’ll write production-level code, move quickly, and collaborate closely with our team of engineers and scientists.
The ideal applicant is someone who is curious, collaborative, and eager to grow, with strong coding skills in Python, Bash, and SQL and experience working on scalable ML infrastructure. An interest in physics is a plus.
If you’re excited about building the backbone of ML systems that power the future of AI, apply now! No up to date resume required!
Salary : $300,000
