Machine Learning Infrastructure Specialist

hace 4 días


Ciudad de México, Ciudad de México Tala A tiempo completo

About Tala

Tala is a pioneering fintech company that empowers the Global Majority by providing innovative financial services. With a strong presence in emerging markets, we have made significant strides in serving millions of customers across three continents.

We are recognized as a leader in our industry, having been named by Fortune Impact 20, CNBC's Disruptor 50, and Forbes' Fintech 50 list for several years. Our mission-driven approach has enabled us to create a unique platform for lending and financial services, enabling individuals to start and expand small businesses, manage daily needs, and pursue their financial goals with confidence.

Our global team operates on a remote-first approach, with offices in key locations worldwide. We are committed to making a positive impact, and our employees share this passion. If you're driven by the desire to make a difference, we'd love to hear from you.

The Role

We're seeking an experienced Senior Cloud Infrastructure Engineer with expertise in MLOps to design, implement, and maintain robust infrastructure and best deployment practices for ML pipelines and models. You will bring valuable experience in Machine Learning, AI infrastructure, and automation, with knowledge of AWS cloud infrastructure and DevOps practices.

Key Responsibilities

  • Design, build, and maintain scalable and robust infrastructure for AI/ML systems, including cloud-based environments, containerization, and orchestration platforms.
  • Develop and implement CI/CD pipelines to automate the deployment, testing, and monitoring of AI/ML models and applications.
  • Evaluate and integrate new tools, technologies, and frameworks to improve the efficiency and effectiveness of our MLOps processes.
  • Design and manage continuous deployment using Kubernetes, ArgoCD, and Jenkins.
  • Maintain related container registry and model registry.
  • Monitor infrastructure utilization and costs pertaining to model training, inference, and GPU utilization.
  • Monitor and troubleshoot AI/ML systems to ensure high availability, performance, and reliability.

Requirements

  • 4+ years of experience as a DevOps Engineer.
  • 1 year of previous experience managing AI/ML infrastructure in public cloud environments.
  • In-depth hands-on experience with at least one public cloud platform, preferably AWS.
  • Experience with Python or any other programming language.
  • Experience with Docker and Kubernetes in production.
  • Experience with Continuous Deployment tools such as Jenkins or ArgoCD.
  • Experience with Logging and Monitoring tools for SaaS such as Sumo, Splunk, Datadog, etc.
  • Proficiency in English.

Compensation and Benefits

We offer a competitive salary range of $160,000 - $200,000 per annum, commensurate with experience. In addition to a comprehensive benefits package, including medical, dental, and vision insurance, we also provide a generous 401(k) matching program, flexible work arrangements, and opportunities for professional growth and development.



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