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Open nowPosted yesterday

Senior Machine Learning Engineer

GEICO281 open roles

Where
Bethesda, MD
Work mode
Hybrid
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Your applicationOpen nowSenior Machine Learning EngineerGEICO · Bethesda, MD

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on GEICO's own form.

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The clock on this job

Early applications get read.

9.6% of postings close within 7 days. Measured by our own scanner across the market. GEICO postings stay open a median of 7 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.9%3 days
  3. 9.6%7 days
  4. 15.6%14 days
  5. 33.9%30 days
This job: posted yesterday

GEICO median: 7 days open

The posting

Why Join GEICO?

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 on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.

Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. 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.

DUTIES: Review the architecture and implementation of machine learning models that solve complex business problems, working closely with Product, Business Units, and Data Science teams. Design and develop scalable infrastructure for model training, automated hyperparameter tuning, and deployment pipelines, ensuring that systems are reliable and performant at scale. Write high-quality, maintainable production-grade code that turns machine learning models into deployable services and APIs. Ensure that code is modular and reusable for future ML projects. Debug and troubleshoot model performance issues, track key metrics, and continuously enhance model reliability, speed, and efficiency in production environments. Review the complete lifecycle of ML models, including monitoring, retraining, and managing versions of models to ensure they continue to meet business needs over time. Promote best practices in software engineering, model development, and deployment. Review technical decision-making processes and foster collaboration within the team. May require pre-hire technical screen. Hybrid Work Policy - 3 days In-office, 2 days remote - Must be able to report to local office. Multiple positions open. Salary $152,838 to $300,000 per year.

REQUIREMENTS: Bachelor’s degree in Computer Science, Business Analytics, Machine Learning, or a related technical field. Four (4) years of experience as a Software Engineer, or related occupation. Four (4) years of experience with: Applying machine learning techniques, including deep learning, reinforcement learning, and NLP in production environments; Machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn for model development; Cloud platforms (AWS, Azure, GCP), including containerization and orchestration tools (Docker, Kubernetes) and cloud-native ML tools (e.g., AWS SageMaker, GCP AI Platform, Azure Machine Learning); Deploying and operating machine learning models in production environments, including system architecture and fault-tolerant design for scalability, reliability, and high availability; Writing production-grade, maintainable code using object-oriented design principles, including SQL, Python, and Spark for data processing supporting model development; Distributed systems, including distributed data processing and microservices architectures used to scale machine learning models in production; MLOps practices, including continuous integration (CI), continuous delivery (CD), automated testing, and deployment pipelines for machine learning models, including data/streaming pipeline tools such as Apache Kafka, Apache Flink, and Spark Streaming; and Setting up, monitoring and logging systems for tracking model performance and resource utilization in production environments.

TO APPLY: Visit, https://careers.geico.com/

The GEICO Pledge:

Great Company: Protecting customers through life’s twists and turns with innovation and integrity.

Great Careers: Personalized development programs, mentorship, and certification assistance.

Great Culture: Inclusive and collaborative culture rooted in shared success.

Great Rewards: Competitive pay, benefits, and flexibility to support your well-being and future.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

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