Senior AI/ML Engineer

Overview

Medallia is the pioneer and market leader in Experience Management. Our award-winning SaaS platform, Medallia Experience Cloud, leads the market in the management of experiences, insights, and actions for candidates, customers, employees, patients, and residents alike.

We believe that every experience is a memory that can last a lifetime. Experiences shape the way people feel about a company. And they greatly influence how likely people are to advocate, contribute, and stay. At Medallia, we are committed to creating a world where organizations are loved by their customers and their employees.

We empower exceptional people to create extraordinary experiences together.

Bring your whole self.

The Role and Team

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

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.

Candidates based in the Buenos Aires vicinity will be prioritized as this role is Hybrid, 3 days per week onsite.

Candidates based in the Mexico City vicinity will be prioritized as this role is Hybrid, 3 days per week onsite.

Qualifications

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.

At Medallia, we celebrate diversity and recognize the value it brings to our customers and employees. Medallia is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age (40 and over), disability, genetic information, veteran status or military service, or any other status protected by state or local law. Individuals with a disability who need an accommodation to apply please contact us at ApplicantAccessibility@medallia.com. For information regarding how Medallia collects and uses personal information, please review our Privacy Policies. Applications will be accepted for 30 days from the date this role was posted or until the role has been filled.

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