Principal Machine Learning Scientist/Engineer - AI Services

GEICO is seeking an experienced lead machine learning scientist to join the AI Solutions org. In this role, you will be a key contributor in building durable services & systems that connects complex data ecosystems and AI/ML models to solve real-world challenges. You will be collaborating with a dynamic team of data scientists and AI-ML experts in crafting and implementing AI solutions that not only enhance our operational efficiencies in measurable ways but also set new benchmarks in industry innovation. 

Responsibilities:  

• AI Systems: Work with Data Scientists and ML Engineers to gather requirements, architect, design, and implement a variety of data-driven systems and platforms ensuring scalability, efficiency, and robustness. Leverage open-source technologies for rapid prototyping & experimentation. Be creative with design but also hands-on with practical concerns. 

• Examples of systems that we develop/enhance include Model orchestration, AB testing, Feature store, Semantic search, GenAI/LLM services, image/document understanding, dashboard & UI services, etc.  

• Feature/Data Engineering: Develop and maintain efficient data pipelines that source structured and unstructured data from various locations, ensuring feature integrity, availability, and optimization. Utilize NLP and generative AI capabilities to extract features from unstructured data for model development.  

• Service Integration: Collaborate with Data Scientists and engineering teams to ensure seamless integration and deployment of AI/ML models into production applications. Work with Product/Engineering leaders to come up with integration designs and project plans and ensure on-time releases.     

• MLOPs: 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, balancing cost effectiveness, architectural simplicity, scalability, extensibility, etc. 

• Technical Leadership: Collaborate with cross-functional teams to ensure alignment, efficacy, and timeliness. Define project roadmaps, establish feature backlogs, and delegate to a small team of junior and mid-level ML scientists for implementation.  Provide guidance on provisioning of environments, rapid deployment of services and application, and monitoring and triage of large-scale production applications. 

• Communication: Translate complex findings into understandable insights and present them to peers, leadership, and business stakeholders.  

• R&D: Stay abreast of the latest developments in AI/ML systems, generative AI, etc. Incorporating new techniques and methodologies into our processes to keep us ahead in the insurance industry.  

Minimum Qualifications 

• A master’s/PhD degree in data science, Computer Science, Statistics, Mathematics, or a related field and at least 6 years of relevant work experience or a Bachelor’s Degree in these fields with at least 8 years of relevant work experience 

• High proficiency (5+ years) in Python and Java, or similar programming languages    

• Track record (5+ years) of key/principal contributor roles in design and implementation of large-scale data-driven productions systems, preferably customer-facing 

• 4+ years’ experience with data orchestration workflow tools such as DBT, Airflow etc. 

• 4+ years’ experience working with big-data technologies/databases, e.g. Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc. 

• 4+ years’ experience working with cloud providers such as AWS and Azure, esp. AI/ML related capabilities such as Aure ML, AWS Sage Maker, Azure OpenAI, AWS Bedrock, etc.  

Preferred Qualifications 

• 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.  

• Experience with building GenAI services & platforms.  

• Domain knowledge on insurance or financial service/fintech sectors.  

• Working knowledge of machine learning techniques and predictive modeling 

Key Competencies 

• Creativity: Able to think outside the box to find innovative solutions to complex problems.  

• Intellectual Curiosity: Passionate about learning and staying updated with the latest developments in the field. 

• Strategic Thinking: Can envision long-term strategies and align day-to-day activities towards achieving them. 

• Decision-Making: Makes sound decisions based on data, analysis, and experience. 

• Adaptability: Thrives in a fast-paced environment, adapting to changing business needs. Make bold experiments and not be afraid of some failures   

• Attention to Detail: Ensures precision and accuracy in all tasks and projects.  

• Interpersonal Sensitivity: Works effectively in team settings, valuing and respecting the views and roles of others.