Senior MLOps Engineer (AI)

TL;DR

Senior MLOps Engineer (AI): Deploying and managing ML model pipelines for generative AI and LLM-based agents with an accent on scalability, observability, and production reliability. Focus on designing CI/CD pipelines, monitoring frameworks for model drift and latency, and automating infrastructure with Docker and Kubernetes.

Location: Buenos Aires, Argentina (hybrid, expect 1-2 days per week in office)

Company

Global technology group delivering high-stakes projects for clients including Google, Snap, PayPal, and Jaguar Land Rover.

What you will do

• Deploy and maintain ML model pipelines using Vertex AI or SageMaker.
• Build and optimize CI/CD for model training, testing, and deployment.
• Design observability frameworks to monitor model accuracy, bias, drift, and latency.
• Manage model versioning, registry, and rollback capabilities.
• Automate deployments with Docker and Kubernetes in cloud environments.
• Collaborate with data engineers on data and model pipelines.
• Implement infrastructure as code using Terraform or CloudFormation.

Requirements

• Must be in Buenos Aires region with ability to attend office 1-2 days per week
• Expertise in MLOps practices and model lifecycle on GCP or AWS.
• Experience with monitoring tools like Prometheus, Grafana, ELK stack.
• Proficiency in Python, Pandas, NumPy, Seaborn for data preprocessing.
• Strong skills in Docker, Kubernetes for containerization and orchestration.
• Ability to automate workflows for efficiency.

Nice to have

• GCP Professional ML Engineer or AWS Certified Solutions Architect.
• Experience with Spark, Hadoop, Dataflow.
• Familiarity with LangChain for LLM operations.

Culture & Benefits

• 10 days PTO + 17 paid public holidays, birthday leave.
• Pension, Law 19032 social security, family allowance, National Employment Fund.
• Accident and life insurance, private medical insurance.
• Work from home allowance, 10 paid learning days per year.
• Bonusly recognition points monthly.