GEICO

Software Engineer – AI/ML Infra

GEICO

full-time

Posted on:

Location Type: Hybrid

Location: Chevy Chase • California, Maryland, New York • 🇺🇸 United States

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Salary

💰 $90,000 - $185,000 per year

Job Level

Mid-LevelSenior

Tech Stack

AzureGoJavaKubernetesOpen SourcePythonRust

About the role

  • Build and scale machine learning infrastructure focused on Large Language Models (LLMs) and AI applications
  • Design and implement scalable infrastructure for training, fine-tuning, and serving open source LLMs
  • Architect and manage Kubernetes clusters for ML workloads
  • Ensure 99.9%+ uptime for ML platforms through robust monitoring
  • Mentor junior engineers and data scientists on platform best practices
  • Collaborate with data scientists and product engineering teams
  • Present technical solutions and platform roadmaps to leadership

Requirements

  • Bachelor’s degree in computer science, Engineering, or related technical field (or equivalent experience)
  • 5+ years of software engineering experience with focus on infrastructure, platform engineering, or MLOps
  • 2+ years of hands-on experience with machine learning infrastructure and deployment at scale
  • 1+ years of experience working with Large Language Models and transformer architectures
  • Proficient in Python; strong skills in Go, Rust, or Java preferred
  • Proven experience working with open source LLMs (Llama 2/3, Qwen, Mistral, Gemma, Code Llama, etc.)
  • Proficient in Kubernetes including custom operators, helm charts, and GPU scheduling
  • Deep expertise in Azure services (AKS, Azure ML, Container Registry, Storage, Networking)
Benefits
  • Comprehensive Total Rewards program that offers personalized coverage
  • Health insurance
  • 401(k) savings plan vested from day one that offers a 6% match
  • Performance and recognition-based incentives
  • Tuition assistance
  • Workplace flexibility as well as GEICO Flex program allowing work from anywhere in the US for up to four weeks per year

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learning infrastructureLarge Language ModelsKubernetesPythonGoRustJavaopen source LLMsMLOpsGPU scheduling
Soft skills
mentoringcollaborationpresentation