AI/ML Infrastructure Architect

hace 2 semanas


Ciudad de México, Ciudad de México Tala A tiempo completo

About Tala

Tala is a fintech company on a mission to empower the global majority by providing accessible financial services. With nearly half a billion dollars in funding, we serve millions of customers across three continents and have been recognized as one of the world's top fintech companies.

Our unique platform enables lending and other financial services globally, allowing individuals in emerging markets to start and grow businesses, manage daily expenses, and achieve their financial goals with confidence.

We're expanding our product offerings, entering new markets, and exploring cryptocurrencies. Our team is diverse and remote-first, with offices in key locations.

The Role

We're seeking an experienced Senior MLOps Engineer to design, implement, and maintain scalable AI/ML infrastructure on AWS cloud platforms. You'll bring expertise in machine learning, AI infrastructure, and automation, as well as hands-on experience with DevOps practices.

Key Responsibilities:

  • Design and build robust, scalable AI/ML systems, including containerization and orchestration platforms.
  • Develop and implement CI/CD pipelines for automated deployment, testing, and monitoring of AI/ML models and applications.
  • Evaluate and integrate new tools, technologies, and frameworks to enhance efficiency and effectiveness of our MLOps processes.
  • Manage continuous deployment using Kubernetes, ArgoCD, and Jenkins.
  • Maintain container registries and model registries.
  • Monitor infrastructure utilization and costs related to model training, inference, and GPU utilization.
  • Troubleshoot AI/ML systems for high availability, performance, and reliability.

Requirements:

  • 4+ years of experience as a DevOps Engineer.
  • 1 year of experience managing AI/ML infrastructure in public cloud environments.
  • In-depth knowledge of at least one public cloud platform, preferably AWS.
  • Experience with Python or other programming languages.
  • Hands-on experience with Docker and Kubernetes in production.
  • Experience with Continuous Deployment tools like Jenkins or ArgoCD.
  • Proficiency in logging and monitoring tools for SaaS platforms.

Compensation: $150,000 - $200,000 per annum, depending on experience and qualifications.



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