Senior MLOps Engineer - Buenos Aires, Argentina

We are looking for an accomplished professional to bridge the gap between machine learning and reliable production operations. You will be responsible for the deployment, monitoring, and lifecycle management of ML models, with a strong focus on generative AI and LLM-based agents. You will ensure that our intelligent systems are scalable, observable, and continuously improving.

About the Company

International technology company that works on complex cloud, data, and AI initiatives for global clients.

We’re currently expanding our engineering presence in Argentina and are looking for a Senior MLOps Engineer to help scale production-grade machine learning systems, with a strong focus on generative AI and modern cloud infrastructure.

This is a highly technical, hands-on role working closely with engineering and data teams on the deployment, automation, monitoring, and continuous improvement of ML platforms and services.

• Deploy and maintain efficient, error-free ML model pipelines using Vertex AI or Sage Maker.

• Establish and optimise CI/CD for the training, testing, and deployment of models.

• Design and deploy observability frameworks to track model accuracy, bias, drift, and latency.

• Manage model versioning and registry, ensuring the ability to roll back when necessary.

• Automate application deployment using Docker and Kubernetes within cloud environments.

• Collaborate with data engineers to build robust data and model pipelines.

• Implement infrastructure as code using Terraform or CloudFormation to manage ML environments.

• Proven expertise in MLOps practices and model lifecycle management on GCP (GCP excluyente).

• Experience designing monitoring systems using Prometheus, Grafana, and the ELK stack.

• Proficient in Python and libraries like Pandas, NumPy, and Seaborn for data preprocessing.

• Strong background in containerisation and orchestration using Docker and Kubernetes.

• Ability to automate complex workflows to save manual effort and improve productivity.

• Fluent/advanced English communication skills are required

Nice to have:

• GCP Professional ML Engineer or AWS Certified Solutions Architect.

• Experience with big data tools like Spark, Hadoop, and Dataflow.

• Familiarity with frameworks like LangChain for LLM operations.

Work Setup

• Hybrid model based in Buenos Aires

• Collaborative engineering environment with international exposure

• Opportunity to join during an important growth stage and influence technical decisions

• Benefits

• Competitive USD compensation under a permanent employment model.

• Private health insurance

• Learning and certification days

• Home office support

• Additional wellness and team-recognition benefits

• Exposure to challenging AI, cloud, and platform engineering projects

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