Description:

Tala is seeking a Senior MLOps Engineer to design, implement, and maintain infrastructure and best deployment practices for ML pipelines and models.
The role involves building and maintaining scalable and robust infrastructure for AI/ML systems, including cloud-based environments, containerization, and orchestration platforms.
Responsibilities include developing and implementing CI/CD pipelines to automate the deployment, testing, and monitoring of AI/ML models and applications.
The engineer will evaluate and integrate new tools, technologies, and frameworks to enhance MLOps processes.
The position requires designing and managing continuous deployment using Kubernetes, ArgoCD, and Jenkins.
The engineer will also maintain related container and model registries, monitor infrastructure utilization and costs, and troubleshoot AI/ML systems to ensure high availability, performance, and reliability.

Requirements:

Candidates must have 4+ years of experience as a DevOps Engineer.
A minimum of 1 year of experience managing AI/ML infrastructure in public cloud environments is required.
In-depth hands-on experience with at least one public cloud platform, preferably AWS, is necessary.
Proficiency in Python or any other programming language is required.
Experience with Docker and Kubernetes in production environments is essential.
Familiarity with Continuous Deployment tools such as Jenkins or ArgoCD is needed.
Experience with logging and monitoring tools for SaaS, such as Sumo, Splunk, or Datadog, is required.
Proficiency in English is mandatory.

Tala offers a remote-first work environment with the flexibility to work from various locations.
The company promotes a diverse and inclusive workplace, valuing different backgrounds, cultures, and experiences.
Employees are part of a mission-driven organization focused on unleashing the economic power of the Global Majority.
Tala provides opportunities for personal and professional growth within a rapidly expanding company in the fintech sector.