At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most.
We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here.
That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.
GEICO AI platform and Infrastructure team is seeking an exceptional Senior ML Platform Engineer to build and scale our machine learning infrastructure with a focus on Large Language Models (LLMs) and AI applications.
This role combines deep technical expertise in cloud platforms, container orchestration, and ML operations with strong leadership and mentoring capabilities.
You will be responsible for designing, implementing, and maintaining scalable, reliable systems that enable our data science and engineering teams to deploy and operate LLMs efficiently at scale.
The candidate must have excellent verbal and written communication skills with a proven ability to work independently and in a team environment.
KEY RESPONSIBILITIES
ML Platform & Infrastructure
Design and implement scalable infrastructure for training, fine-tuning, and serving open source LLMs (Llama, Mistral, Gemma, etc.)Architect and manage Kubernetes clusters for ML workloads, including GPU scheduling, autoscaling, and resource optimizationDesign, implement, and maintain feature stores for ML model training and inference pipelinesBuild and optimize LLM inference systems using frameworks like vLLM, TensorRT-LLM, and custom serving solutionsEnsure 99.9%+ uptime for ML platforms through robust monitoring, alerting, and incident response proceduresDesign and implement ML platforms using DataRobot, Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure Container InstancesDevelop and maintain infrastructure using Terraform, ARM templates, and Azure DevOpsImplement cost-effective solutions for GPU compute, storage, and networking across Azure regionsEnsure ML platforms meet enterprise security standards and regulatory compliance requirementsEvaluate and potentially implement hybrid cloud solutions with AWS/GCP as backup or specialized use casesDevOps & Platform Engineering
Design and maintain robust CI/CD pipelines for ML model deployment using Azure DevOps, GitHub Actions, and MLOps toolsImplement automated model training, validation, deployment, and monitoring workflowsSet up comprehensive observability using Prometheus, Grafana, Azure Monitor, and custom dashboardsContinuously optimize platform performance, reducing latency and improving throughput for ML workloadsDesign and implement backup, recovery, and business continuity plans for ML platformsTechnical Leadership & Mentoring
Mentor junior engineers and data scientists on platform best practices, infrastructure design, and ML operationsLead comprehensive code reviews focusing on scalability, reliability, security, and maintainabilityDesign and deliver technical onboarding programs for new team members joining the ML platform teamEstablish and champion engineering standards for ML infrastructure, deployment practices, and operational proceduresCreate technical documentation, runbooks, and deliver internal training sessions on platform capabilitiesCross-Functional Collaboration
Work closely with data scientists to understand requirements and optimize workflows for model development and deploymentCollaborate with product engineering teams to integrate ML capabilities into customer-facing applicationsSupport research teams with infrastructure for experimenting with cutting-edge LLM techniques and architecturesPresent technical solutions and platform roadmaps to leadership and cross-functional stakeholdersREQUIRED QUALIFICATIONS
Experience & Education
Bachelor’s degree in computer science, Engineering, or related technical field (or equivalent experience)8+ years of software engineering experience with focus on infrastructure, platform engineering, or MLOps3+ years of hands-on experience with machine learning infrastructure and deployment at scale2+ years of experience working with Large Language Models and transformer architecturesTechnical Skills - Core Requirements
Proficient in Python; strong skills in Go, Rust, or Java preferredProven 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 schedulingDeep expertise in Azure services (AKS, Azure ML, Container Registry, Storage, Networking)Experience implementing and operating feature stores (Chronon, Feast, Tecton, Azure ML Feature Store, or custom solutions)Hands-on experience with inference optimization using vLLM, TensorRT-LLM, Triton Inference Server, or similarDevOps & Platform Skills
Advanced experience with Azure DevOps, GitHub Actions, Jenkins, or similar CI/CD platformsProficiency with Terraform, ARM templates, Pulumi, or CloudFormationDeep understanding of Docker, container optimization, and multi-stage buildsExperience with Prometheus, Grafana, ELK stack, Azure Monitor, and distributed tracingKnowledge of both SQL and NoSQL databases, data warehousing, and vector databasesLeadership & Soft Skills
Demonstrated track record of mentoring engineers and leading technical initiativesExperience leading design reviews with focus on compliance, performance, and reliabilityExcellent ability to explain complex technical concepts to diverse audiencesStrong analytical and troubleshooting skills for complex distributed systemsExperience managing cross-functional technical projects and coordinating with multiple stakeholdersPREFERRED QUALIFICATIONS
Advanced Experience
Master’s degree in computer science, Machine Learning, or related field8+ years of platform engineering or infrastructure experienceExperience with Staff Engineer or Tech Lead roles in ML/AI organizationsBackground in distributed systems and high-performance computingOpen-source contributions to ML infrastructure projects or LLM frameworksSpecialized Skills
Multi-Cloud Experience: Hands-on experience with Azure, AWS (SageMaker, EKS) and/or GCP (Vertex AI, GKE)Experience with specialized hardware (A100s, H100s, TPUs, TEEs) and optimizationRLHF & Fine-tuning: Experience with Reinforcement Learning from Human Feedback and LLM fine-tuning workflowsExperience with Milvus, Pinecone, Weaviate, Qdrant, or similar vector storage solutionsDeep experience with MLflow, Kubeflow, DataRobot, or similar platformsIndustry Knowledge
Understanding of AI safety principles, model governance, and regulatory complianceBackground in regulated industries with understanding of data privacy requirementsExperience supporting ML research teams and academic partnershipsDeep understanding of GPU optimization, memory management, and high-throughput systemsLocation
Remote
The GEICO Pledge:
Great Company: At GEICO, we help our customers through life’s twists and turns.
Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.
We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success.
From day one, you’ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people’s lives.
Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career – and your potential – in mind.
You’ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.
Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset.
Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives.
Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.
Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.Access to additional benefits like mental healthcare as well as fertility and adoption assistance.Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.