GEICO

Senior Staff Machine Learning Engineer

GEICO

full-time

Posted on:

Location Type: Hybrid

Location: Palo Alto • California, Washington • 🇺🇸 United States

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Salary

💰 $150,000 - $300,000 per year

Job Level

Senior

Tech Stack

AWSAzureCloudJavaKubernetesPythonReactSDLC

About the role

  • Own design, development and maintenance of high-performance AI solutions that utilize agentic workflows to deliver concrete business value for internal stakeholders.
  • Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs.
  • Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
  • Integrate and build solutions using GEICO AI platform architecture.
  • Partner with platform teams to communicate requirements, understand current capabilities and gaps, and contribute to platform development.
  • Ideate and build first-of-its-kind solutions within GEICO, with a deep understanding of business and technical processes, applications, and architecture to guide development.
  • Drive the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
  • Take ownership in project planning and stakeholder management, ensuring the efficient allocation of resources and timely delivery of solutions.
  • Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture.

Requirements

  • 10+ years of experience designing and building scalable production AIML applications and systems in cloud environments.
  • Proficient in Python, Java and similar general-purpose programming languages.
  • 7 years managing end-to-end software development life cycle (e.g. CICD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for backend systems and APIs.
  • 5 years in training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs.
  • 5 years owning end-to-end development, monitoring, maintenance , and continuous improvement of scalable, robust AIML applications.
  • Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field.
  • 5 years interfacing directly with internal business stakeholders and/or external stakeholders on AIML initiatives.
  • 5 years working with cloud provider solutions such as Azure and AWS.
  • 4 years with tools that power LLM-based AI agents: eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc.
  • 3 years building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments.
  • 2 years of ideating, integrating, and designing applications and frontends using React or similar.
  • Strong communication and problem-solving skills to excel in dynamic, cross-functional and ambiguous decision-making environments.
Benefits
  • 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.

Applicant Tracking System Keywords

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

Hard skills
PythonJavaAIML applicationsCICD pipelinesKubernetesreal-time inferencingbatch inferencingLLMsReactcloud environments
Soft skills
communicationproblem-solvingstakeholder managementmentoringcollaborationproject planningresource allocationtechnical visionteam culturecross-functional collaboration