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DevOps Engineer (ML-Ops)

An AI technology company making AI accessible and actionable for businesses through a no-code platform for B2B clients.
DevOps
Mid-Level Software Engineer
Remote
3+ years of experience
AI · Enterprise SaaS
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Description For DevOps Engineer (ML-Ops)

Join Synthflow.ai, a pioneering company in the AI technology space that's revolutionizing how businesses interact with AI through their innovative no-code platform. As a DevOps Engineer specializing in MLOps and LLM Ops, you'll be at the forefront of developing and managing the infrastructure that powers our AI-driven speech technology and large language models.

The role offers a unique opportunity to work with cutting-edge AI technology while building scalable solutions that impact businesses globally. You'll be responsible for creating and maintaining robust CI/CD pipelines, optimizing model deployment processes, and ensuring the reliability of our AI infrastructure. With a minimum of 3 years of experience required, you'll bring your expertise in cloud services, containerization, and MLOps to help shape the future of AI technology.

Working at Synthflow AI means joining a dynamic, remote-first environment where innovation and creativity are encouraged. The company offers a comprehensive benefits package including competitive compensation, equity options, and health benefits. You'll have the flexibility to work from anywhere while contributing to projects that have global impact.

The ideal candidate will combine technical expertise in DevOps and MLOps with strong communication skills, enabling effective collaboration across technical and non-technical teams. If you're passionate about AI technology and want to be part of a fast-growing startup that's making AI accessible to businesses of all sizes, this role offers the perfect opportunity to make a significant impact while advancing your career.

Last updated 4 months ago

Responsibilities For DevOps Engineer (ML-Ops)

  • Develop and manage scalable and secure infrastructure for deploying TTS, STT, and LLM applications
  • Create and maintain CI/CD pipelines for continuous integration and deployment of AI models
  • Work with ML engineers to optimize training, validation, and deployment of speech and language models
  • Monitor and analyze system performance and resolve issues
  • Implement best practices in cloud technology, containerization, and MLOps/LLM Ops tools

Requirements For DevOps Engineer (ML-Ops)

Python
Kubernetes
  • Bachelor's degree in Computer Science, Engineering, or related technical field
  • Minimum of 3 years experience in DevOps, with MLOps and LLM Ops exposure
  • Strong programming and scripting skills in Python
  • Proficiency with cloud services (AWS, GCP, Azure) for ML and LLM environments
  • Expertise in Docker and Kubernetes
  • Strong communication skills
  • Experience in infrastructure management and operations for ML and LLM frameworks

Benefits For DevOps Engineer (ML-Ops)

Medical Insurance
Equity
  • Competitive salary
  • Comprehensive health benefits
  • Equity options
  • Flexible work arrangements
  • Remote work opportunities
  • Stock options
  • Direct impact and project ownership
  • Cutting-edge technology work
  • Collaborative team culture

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