Senior Machine Learning Scientist/Engineer - AI Engineering

$90,000 - $260,000/Yr

Geico - Chevy Chase, MD

Full-time - Mid Level

Chevy Chase, MD

5,001-10,000 employees

Insurance Carriers and Related Activities

About the position

As an AI Systems Engineer at GEICO, you will play a pivotal role in collaborating with Data Scientists and ML Engineers to gather requirements, architect, design, and implement a variety of AI/ML capabilities and platforms. Your focus will be on ensuring scalability, efficiency, and robustness in the systems we develop. You will leverage open-source technologies for rapid prototyping and experimentation, allowing for creative design while also addressing practical concerns. The systems you will work on include Semantic search, GenAI/LLM-based virtual agent services, image/document understanding, Model orchestration, AB testing, and Feature store, among others. In addition to system development, you will be responsible for service integration, collaborating with Data Scientists and engineering teams to ensure seamless integration and deployment of AI/ML models into production applications. You will work closely with Product and Engineering leaders to devise integration designs and project plans, ensuring timely releases. Your role will also encompass data engineering, where you will develop and maintain efficient data pipelines that source structured and unstructured data from various locations, ensuring data availability and integrity. You will establish MLOps best practices, focusing on the software development lifecycle (SDLC) and site reliability engineering (SRE) to ensure stable operations of production AI systems. This includes leading the evaluation, procurement, and deployment of specialized AI infrastructure components such as GPU clusters and vector databases, balancing cost-effectiveness, architectural simplicity, scalability, and extensibility. Communication will be key, as you will translate complex findings into understandable insights and present them to peers, leadership, and business stakeholders. As a technical leader, you will collaborate with cross-functional teams to ensure alignment, efficacy, and timeliness. You will define project roadmaps, establish feature backlogs, and lead a small team of ML scientists for implementation, driving innovation and excellence in AI/ML solutions.

Responsibilities

• Work with Data Scientists and ML Engineers to gather requirements, architect, design, and implement AI/ML capabilities and platforms.
• Leverage open-source technologies for rapid prototyping and experimentation.
• Collaborate with Data Scientists and engineering teams to ensure seamless integration and deployment of AI/ML models into production applications.
• Develop and maintain efficient data pipelines that source structured and unstructured data from various locations, ensuring data availability and integrity.
• Establish SDLC and SRE best practices to ensure stable operations of production AI systems.
• Lead the evaluation, procurement, and deployment of specialized AI infrastructure components such as GPU clusters and vector databases.
• Translate complex findings into understandable insights and present them to peers, leadership, and business stakeholders.
• Collaborate with cross-functional teams to ensure alignment, efficacy, and timeliness.
• Define project roadmaps, establish feature backlogs, and lead a small team of ML scientists for implementation.

Requirements

• A master's/PhD degree in data science, Computer Science, Statistics, Mathematics, or a related field and at least 3 years of relevant work experience, or a bachelor's degree in these fields with at least 5 years of relevant work experience.
• High proficiency (3+ years) in Python, Java or equivalent programming languages.
• Track record (2+ years) of key/principal contributor roles in design and implementation of production AI/ML systems, preferably customer-facing.
• 2+ years' experience working with big-data technologies/databases, e.g. Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc.
• 2+ years' experience working with cloud providers such as AWS and Azure, especially AI/ML related capabilities such as Azure ML, AWS Sage Maker, Azure OpenAI, AWS Bedrock, etc.
• Experience with building GenAI services & platforms.

Nice-to-haves

• 3+ years' experience training, finetuning and evaluating AI/ML models (traditional ML, Deep learning and LLMs).
• 3+ years' experience in building, deploying, and maintaining AI-ML pipelines and API services on both CPU and GPU-based infrastructure.
• 3+ years' experience in processing unstructured data.
• Experience in designing and building metrics dashboard and UI applications for AI/ML systems, using frameworks such as Streamlit, Dash, Shiny, etc.
• Domain knowledge on insurance or financial service/fintech sectors.

Benefits

• Premier Medical, Dental and Vision Insurance with no waiting period
• Paid Vacation, Sick and Parental Leave
• 401(k) Plan
• Tuition Reimbursement
• Paid Training and Licensures