Superteams.ai helps businesses build agentic systems, deploy private LLMs, and power next-gen AI workflows. Our company blends AI expertise, cloud infrastructure, and open-source technologies to help clients build, scale, and maintain custom AI solutions across sectors like education, climate, and enterprise SaaS.

Our work spans a wide spectrum of Generative AI applications -  from LLMs and vision models to audio synthesis and predictive analytics. If you’re passionate about infrastructure that supports cutting-edge AI systems, you’ll thrive here.

What You’ll Do

As a MLOps Engineer

, you will play a critical role in deploying, managing, and scaling infrastructure that powers AI systems. You’ll work closely with AI developers and product teams to automate deployment, monitor performance, and ensure uptime and reliability across various environments.

Key Responsibilities

• Set up and manage cloud infrastructure (AWS, GCP, or Azure) for AI and data applications.

Must-Have Skills

Nice to Have

• Experience with vLLM for LLM serving and handling batching, queueing, retries and error handling with LLM requests.

• Working knowledge of Python

  for scripting and automation. You should be able to understand Python code, debug it to some extent and fix issues that may happen in production.

What You’ll Gain

• Exposure to the latest in Generative AI and agentic systems.
• Hands-on experience with AI devops challenges: model hosting, scaling inference, observability in multimodal systems, and more.
• Opportunity to contribute to open-source AI infrastructure tools.
• A fast-paced, collaborative environment where learning and innovation are at the core.

If you're excited to build scalable infrastructure that enables cutting-edge AI, we’d love to hear from you.