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