Software Engineer Intern – Kubernetes & Inferencing Infrastructure

Gruve Texas 34 days ago

engineering

About Gruve

Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.

Location: Houston, TX
Team: Inferencing & Infrastructure
Employment Type: Part-Time Internship (approximately 20 hours per week; minimum of 10 hours per week on-site)
Compensation: $14-$28 per hour

About the Role

Gruve is seeking a part-time Software Engineer Intern with interest in Kubernetes, container orchestration, and distributed systems to support the infrastructure powering our Inferencing Services platform. In this role, you will assist in designing and implementing a robust on-demand container model for AI workloads, enable multi-tenancy with strong isolation and security, and contribute to performance and cost optimization efforts.

This internship is an excellent opportunity for students or early-career engineers who want hands-on experience at the intersection of infrastructure and AI application development, while building proficiency in Kubernetes, Python, and Go.

Key Responsibilities

Support the design, build, and maintenance of Kubernetes-based infrastructure for AI inferencing services.
Assist in developing multi-tenant microservices to support customer isolation and scalability.
Contribute to applying security best practices for inference workloads and model protection.
Help with optimization projects such as container startup times, memory footprint, and compute utilization.
Write and maintain code in Python and Go, and support automation using Terraform, Helm, etc.

Basic Qualifications

Familiarity with Kubernetes concepts (operators, CRDs, Helm, networking).
Exposure to container orchestration for AI/ML workloads (e.g., TensorRT, ONNX Runtime, PyTorch).
Proficiency in Python or Go for infrastructure or service development (academic or project experience acceptable).
Understanding of multi-tenant system design and workload isolation.
Interest in GPU/accelerator scheduling and performance optimization.

Preferred Qualifications

Currently pursuing a bachelor’s or master’s degree in Computer Science, Electrical Engineering, or a related technical field, with an expected graduation date of December 2025, May 2026, or December 2026.
Availability to begin the internship as soon as possible is preferred, though candidates seeking a Summer 2026 start date will also be considered.
Students currently enrolled at Rice University are strongly encouraged to apply.
Hands-on experience deploying AI/ML inferencing in academic, project, or internship environments.
Exposure to edge inference architectures or low-latency workloads.
Familiarity with observability tools such as Prometheus, Grafana, or OpenTelemetry.
Knowledge of service mesh technologies including Istio, Linkerd, or Cilium.
Prior contributions to open-source Kubernetes or cloud-native projects are a plus.

Opportunity for Growth

This internship has the potential to transition into a full-time position based on performance, business needs, and mutual interest.

Why Gruve

At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.

Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.