ML Engineer, Cloud Platform

About the role

You will have ownership over designing, building, and scaling the core infrastructure that brings Prior Labs' foundation models to the world. This is a unique opportunity to make fundamental architectural decisions, establish engineering best practices from the ground up, and profoundly shape the technical direction for serving state‑of‑the‑art AI.

You'll work directly with world‑class AI researchers, translating cutting‑edge models into reliable, scalable production systems. This role offers significant autonomy and impact, with clear paths to specialize in areas you're passionate about (like ML infrastructure or core backend systems) or grow into a technical leadership position as our team expands. You won't just be implementing features; you'll be building the backbone of our company.

• Architect & Design: Design robust, scalable, and secure backend systems and production‑grade APIs for serving and fine tuning our foundation models.

• Build & Implement: Develop high‑quality, maintainable code (Python/FastAPI experience highly valued) for core backend services.

• Own Infrastructure: Design, deploy, and manage core infrastructure on cloud platforms, focusing on reliability, monitoring, observability, and cost‑efficiency.

• Core MLOps Concepts: Understanding of the entire machine learning lifecycle (MLLC) from data ingestion and preparation to model deployment, monitoring, and retraining.

• Ensure Compliance & Security: Implement secure, GDPR‑compliant systems, including data storage, access control, usage tracking, and quota management.

• Champion Best Practices: Drive high standards for testing, CI/CD, documentation, and security within the engineering team.

• 3+ years of professional experience in a cloud engineering, data platform, or SRE role, with a proven track record of managing production infrastructure.

• Proven experience building and maintaining data‑intensive systems
  , with a strong understanding of data modeling, storage, and processing technologies.

• Strong, hands‑on experience with Infrastructure as Code (IaC) using tools like Terraform.

• Significant experience with containerization and orchestration technologies (
  Docker, Kubernetes
  ).

• Proficiency in Python.

• Experience building or managing infrastructure specifically for machine learning (MLOps, model serving frameworks, feature stores, data pipelines).

• Hands‑on experience with modern data warehousing and processing platforms like Databricks, Snowflake, or Big Query.

• Contributions to relevant open‑source projects.

We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box."

We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are.

We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.