About the role

Role overview

Join super.AI as a Machine Learning Engineer to measure and ensure the quality of AI workloads for enterprise customers. You will deploy and manage production AI systems, build scalable software, and help fine-tune and deploy Large Language Models.

Responsibilities

Measure and ensure quality of AI workload outputs for enterprise customers
Deploy and manage production workloads for a global customer base
Write, rewrite, and extend Python code and run local testing (e.g., using Jupyter Notebook)
Integrate AI cloud solutions and adapt them to large-scale use cases
Perform prompt engineering and fine-tune and deploy LLMs
Build software that scales to high-load demands
Deploy Python services using containers

Requirements

3–5 years of professional software development experience
Solid understanding of machine learning principles
Proficiency with REST APIs
Experience with container frameworks such as Docker or Kubernetes
Familiarity with distributed systems and cloud services (AWS/Azure/GCP)
Ability to organize and prioritize competing workloads
Proven ability to work backwards from customer needs to deliver AI features

Nice-to-haves / alignment

Strong collaboration and ownership mindset (taking responsibility, meritocracy)
Affinity for learning and automating where possible

About super.AI

super.AI helps enterprise customers run high-quality AI workloads. The company operates and improves production AI systems, including deploying scalable machine-learning and large language model solutions. It focuses on reliability, integration with cloud services, and performance for high-load customer demand.