Senior AI/ML Engineer

AI/ML Engineer — Senior

Location : Remote (Mexico /Argentina)

Overview

We are looking for a Senior AI/ML Engineer to join our Medallia AI Platform team and lead the evolution of our AI platform.

The Role

As a Senior AI/ML Engineer on the AI Platform team, you will architect and develop the building blocks of our next-generation AI products. You will work with cross-functional teams to deliver world-class AI capabilities to enterprise customers.

Responsibilities

• Lead the evolution of our AI/ML platform services, ensuring compliance, security, and performance standards.
• Design and implement in-house and cloud-native ML infrastructure.
• Monitor, maintain, and optimize deployed models and ML pipelines.
• Build and maintain secure data pipelines across national boundaries.
• Collaborate with product and design teams to build innovative features for the Customer Experience space.
• Architect scalable solutions for large-scale data processing made available to clients with high performance.
• Design and implement APIs to power front-end applications.
• Identify process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for greater scalability.
• Participate in a scheduled on-call rotation to maintain the availability and reliability of both internal platforms and customer-facing production systems.

Minimum Qualifications

• BA/BS degree in Computer Science or a related technical discipline, or equivalent practical experience.
• 5+ years of software development in production environments using Python, Java, or Scala.
• Microservices development experience.
• Demonstrated experience deploying and operating services on Kubernetes (K8s); familiarity with K8s-based deployment frameworks in regulated environments.
• Demonstrated experience with distributed systems: Spark, Hadoop, Kafka.
• Demonstrated experience with Relational SQL including Postgres.
• Demonstrated experience with code quality best practices and testing architectures on large codebases.

Preferred Qualifications

• Familiarity with AWS services (EC2, S3, IAM, VPC, EKS, SageMaker) for cases where native AWS deployments are required outside the company's K8s framework.
• Experience with ML model serving platforms: TensorFlow Serving, TensorRT, Triton, KServe.
• Experience with data pipeline and workflow management tools such as Airflow or Kubeflow.
• Knowledge about Django or Spring framework.
• Experience with NoSQL databases including ElasticSearch.