We Are Hiring || Senior AI/ML Engineer || Remote || (Mexico /Argentina)
Role: Senior AI/ML Engineer
Location: Remote (Mexico /Argentina)
Jop Type: Contract
Overview
We are looking for a Senior AI/ML Engineer to join our Client’s 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.