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Syntiant

Edge AI processors and scalable models

DevOps Machine Learning Infrastructure Engineer Intern

DevOps EngineeringUpdated on Nov 11
InternshipIrvine, CA, USANo salary listedIn-person

About the Job

Requirements

  • The candidate must be pursuing a Bachelor's or Master's degree in Computer Science, or have equivalent work experience, with relevant coursework, research, or project experience.
  • The candidate must be proficient in Python and familiar with FastAPI for API development.
  • The candidate should have exposure to AWS EKS, including deploying, scaling, and managing Kubernetes clusters.
  • The candidate must be familiar with containerization technologies such as Docker and Kubernetes.
  • The candidate should have exposure to cloud infrastructure services such as S3, RDS, and VPCs.
  • The candidate must be familiar with CI/CD tools such as GitLab CI/CD or Jenkins.
  • The candidate must be familiar with database systems including MongoDB, PostgreSQL, and NFS.
  • The candidate should have exposure to on-premises storage solutions such as Ceph.
  • The candidate must be familiar with Linux system administration.
  • The candidate must be willing to learn to write clean, maintainable code and perform thorough testing.
  • The candidate should have exposure to cloud-native observability tools such as Prometheus and Grafana.
  • The candidate should be familiar with Kubernetes operators and Helm charts.
  • The candidate should have exposure to on-premises container orchestration using Kubernetes or similar technologies.
  • The candidate should have exposure to DevOps best practices and infrastructure as code using Terraform or Ansible.

Responsibilities

  • Develop, maintain, and optimize RESTful APIs using Python and FastAPI.
  • Deploy and manage applications on AWS EKS, ensuring high availability, scalability, and performance.
  • Integrate with data sources and services such as MongoDB and PostgreSQL for efficient data storage and retrieval.
  • Implement CI/CD pipelines to automate testing and deployment processes.
  • Collaborate across teams to ensure seamless integration of cloud-native tools and practices.
  • Maintain on-premises servers running Ceph, PostgreSQL, and NFS services.
  • Troubleshoot and resolve issues across development, staging, and production environments.
  • Participate in code reviews, pair programming, and knowledge-sharing sessions.

About the Company

Syntiant

Edge AI processors and scalable models

Syntiant creates edge AI hardware and software that run deep learning models on-device in power-limited products. Its Neural Decision Processors and scalable neural models are designed to operate in compute-constrained environments and can run on a wide range of hardware—from the smallest MCUs to large GPUs—without relying on cloud servers. This lets devices like smart home gear, cars, personal devices, and industrial products perform intelligent tasks locally, saving battery power and reducing cloud costs. Syntiant differentiates itself by offering hardware-agnostic, scalable ML models that deliver much higher efficiency and throughput for edge inference across diverse platforms. The company’s goal is to enable practical on-device AI across multiple industries, improving user experience while lowering energy usage and cloud dependence.

Company size
201-500
Company stage
Late Stage VC
Total funding
$120.1M
Headquarters
Irvine, CA
Founded
2017

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