Distinguished Engineer, AI Applications

GEICO•Palo Alto, CA

5d•$210,000 - $350,000

About The Position

As a Distinguished Machine Learning Engineer, you will be a senior technical leader responsible for informing the company’s strategic machine learning initiatives. In this role, you will architect scalable machine learning systems, partner with leadership to align ML efforts with business objectives and oversee the entire lifecycle of machine learning models. You will lead cross-functional teams, explore cutting-edge techniques, and ensure that machine learning systems are stable, reliable, robust, interpretable, and compliant with industry standards.

Requirements

B. Sc. degree in Machine Learning, Computer Science, Statistics, Mathematics, or related field
10 + years of experience in design and implementation of machine learning systems
Experience with data governance, security, and regulatory compliance in AI systems, including ensuring fairness, transparency, and ethical considerations in ML models.
Extensive knowledge of machine learning algorithms, large-scale data pipelines, and real-time ML serving systems
Proven ability to scale ML models in production environments and design robust monitoring and alerting systems.
Expertise in cross-functional leadership, mentoring, and delivering high-impact machine learning projects
10+ years of proficiency in Python, Java, or similar programming languages.
10+ years of experience with data orchestration workflow tools (e.g., DBT, Airflow)
8+ years of experience with big-data technologies (e.g., Spark, MongoDB, ElasticSearch, Snowflake, Neo4j).
Extensive experience working with cloud providers like AWS and Azure, with a focus on machine learning services (e.g., SageMaker, Azure ML, AWS Bedrock).

Responsibilities

Explore and integrate new machine learning techniques into the company’s portfolio to drive innovation and stay at the forefront of ML technology.
Evangelize and inspire best practices across AI/ML, fostering a culture of craftsmanship and innovation.
Assist in setting the vision and strategy for machine learning and AI initiatives within the organization.
Lead the architecture design for the company’s key machine learning initiatives, ensuring systems are highly scalable, efficient, and aligned with industry best practices.
Oversee the integration of cutting-edge ML techniques into existing workflows.
Develop and implement frameworks for model interpretability, fairness, and explainability, ensuring compliance with ethical standards, regulatory requirements, and industry best practices.
Design robust systems for monitoring and maintaining machine learning models in production, including setting up alerting mechanisms, retraining pipelines, and model governance structures.