ML Engineer, Cloud Platform

PriorLabs GmbH; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

PriorLabs GmbH is seeking an experienced Cloud Infrastructure Engineer to design, build, and scale the core backend and production systems powering our foundation models. You will work closely with AI researchers to translate cutting‑edge research into reliable, scalable services and automated pipelines.

In this role you will own cloud infrastructure, implement IaC with Terraform, and drive best practices for testing, CI/CD, and security across the engineering team, enabling robust deployment

Qualifications

• 3+ years of professional experience in cloud engineering, data platform, or SRE roles.
• Proven ability to design and maintain data‑intensive systems.
• Hands‑on experience with IaC using Terraform.
• Strong containerization/orchestration experience (Docker, Kubernetes).
• Proficiency in Python and building production backend services.

Responsibilities

• Architect, design, and scale robust backend systems and APIs for serving foundation models.
• Develop high‑quality, maintainable code (Python/FastAPI) for core services.
• Own infrastructure deployment and operations on cloud platforms with focus on reliability and cost‑efficiency.
• Understand the end‑to‑end ML lifecycle including data prep, deployment, monitoring, and retraining.
• Ensure GDPR‑compliant systems with secure data storage, access control, and auditing.

Skills

Python

Cloud infrastructure design

SRE practices

CI/CD

Security & compliance

Team collaboration

Tools

Terraform

Docker

Kubernetes

Databricks

Snowflake

BigQuery

Job description

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.

What You’ll Do

• Architect & Design: Design robust, scalable, and secure backend systems and production‑grade APIs for serving and finetuning 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.

Qualifications

• 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.

What Sets You Apart

• 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 BigQuery.

• Contributions to relevant open‑source projects.

Our Commitments

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.