Senior Machine Learning Engineer

GEICO • Bethesda, MD

1d • $115,000 - $230,000 • Remote

About The Position

GEICO is redefining the insurance landscape through cutting-edge Artificial Intelligence, and the AI Research team is driving this transformation. We are developing innovative, centralized, real-time AI solutions to solve complex business challenges and deliver advanced capabilities across claims, customer interactions, and operational efficiency. As a Senior Machine Learning Engineer, you will play a pivotal role as a technical leader, designing, deploying, and managing production-grade ML systems that directly impact core business functions. This position is ideal for engineers who have experience shipping ML systems and seek greater ownership, technical depth, and significant business influence. This is a hands-on opportunity for those passionate about scalable architectures, model robustness, and delivering operational excellence in advanced AI systems.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field (Master’s or PhD a plus).
• 6+ years of experience building and deploying machine learning systems in production environments.
• Strong proficiency in Python (and/or Java) and production-grade software engineering practices.
• Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Hands-on experience with the full ML lifecycle, including deployment, monitoring, and retraining.
• Hands-on experience building and deploying LLM-based applications, including prompt design, retrieval-augmented generation (RAG), model evaluation, and production integration.
• Familiarity with distributed data systems and modern ML infrastructure.

Nice To Haves

• Domain experience in AI Research, Predictive Modeling, Automation, or Decision Intelligence.
• Experience with fine-tuning, adaptation, evaluation frameworks, and safety/guardrails for large language model (LLM) systems.
• Familiarity with real-time ML serving architectures, feature stores, and low-latency systems.
• Exposure to advanced modeling techniques, such as deep learning, reinforcement learning, or natural language processing.
• Experience with big-data and pipeline technologies (Spark, Snowflake, Airflow, DBT).
• Knowledge of model explainability, fairness, and governance in regulated industries.

Responsibilities

• Own End-to-End Production ML Systems: Design, implement, and deploy machine learning models and features for diverse AI applications including predictive analytics, automation, and decision support.
• Manage the complete ML lifecycle: data ingestion, feature engineering, training, evaluation, deployment, monitoring, and retraining.
• Continuously advance model performance, reliability, and interpretability in production environments.
• Build Scalable AI ML Pipelines: Develop scalable batch and real-time pipelines to support high-throughput AI workflows and applications.
• Optimize ML serving systems for speed, reliability, and cost-effectiveness.
• Collaborate with platform teams to enhance feature stores, model registries, and deployment infrastructure for AI solutions.
• Drive Technical Excellence: Author high-quality, well-tested, and maintainable code in Python (and/or Java).
• Contribute to shared ML frameworks, tooling, and promote engineering best practices across the research team.
• Engage in architecture discussions, design reviews, and technical roadmap development for AI initiatives.
• Mentor & Collaborate Across Teams: Mentor junior engineers (MLE I/II), providing code reviews, guidance, and technical leadership.
• Work closely with data scientists, software engineers, operations, and product teams to integrate ML solutions into real-world applications.
• Translate complex business and technical challenges into actionable ML solutions.
• Operate Reliable ML in a Regulated Environment: Ensure ML systems adhere to high standards for monitoring, alerting, security, privacy, and compliance.
• Support incident response and maintain production reliability for AI-driven systems.
• Contribute to model governance, explainability, and responsible AI practices.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior