Description

You will design, develop, and maintain a scalable AI platform for investment management technology.

Responsibilities

• Implement and manage Kubernetes clusters to deploy AI models.
• Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure.
• Maintain automated pipelines for continuous training, testing, and deployment of machine learning models.
• Translate business and functional requirements into scalable technical designs.
• Troubleshoot and resolve platform performance and reliability issues.

Required Skills

• 10+ years of experience in software and platform engineering.
• Proficiency in Rust and C++.
• Strong experience with Kubernetes, including Helm, Kustomize, and CRDs.
• Hands-on experience with AWS, GCP, or Azure.
• Expertise in containerization using Docker and containerd.
• Proficiency with CI/CD tools including Jenkins, GitHub Actions, and ArgoCD.
• Experience with Infrastructure as Code (IaC) using Terraform or CloudFormation.
• Knowledge of Python and data science tools such as PyTorch, Jax, and Numpy.
• Understanding of distributed systems, cluster orchestration, and networking security.
• Experience with monitoring tools like Prometheus and Grafana.

Preferred Skills

• Experience with GPU orchestration and optimization in Kubernetes.
• Knowledge of MLOps, model lifecycle pipelines, and fine-tuning.
• Familiarity with Kafka, Spark, Dask, or Cassandra.

Key Skills

Education

Any Graduate