GEICO is seeking an experienced Senior Manager to join the GEICO AI Org. In this role, you will lead a team of Machine Learning Scientists / Engineers and build durable services & systems that connect 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.
Key Responsibilities :
AI Systems : Lead design, architecting, and implementation of 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 Pipelines : Lead development and maintenance of efficient data pipelines that source structured and unstructured data from various locations, ensuring feature integrity and availability.
Utilize NLP and generative AI capabilities to extract features from unstructured data for model development.
Service Integration : Collaborate with Data Science and Machine learning 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, and extensibility.
- Technical Leadership : Collaborate with cross-functional teams and leadership 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 current with emerging AI technologies and incorporate them into the development process. Proactively identify opportunities for innovation and efficiency in AI solutions.
Minimum Qualifications
- A Master’s / PhD degree in data science, Computer Science, Statistics, Mathematics, or a related field and at least 8 years of relevant work experience or a bachelor’s degree in these fields with at least 10 years of relevant work experience
- High proficiency (7+ years) in Python and Java, or similar programming languages
- Track record (7+ years) of AI system design and implementation of large-scale data-driven productions systems, preferably customer-facing
- 6+ years of experience of leading a high-functioning team of Machine Learning Engineers / Scientists
- 6+ years’ experience with data orchestration workflow tools such as DBT, Airflow etc.
- 6+ years’ experience working with big-data technologies / databases, e.g., Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc.
- 6+ 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
- 5+ years’ experience in building, deploying, and maintaining AI-ML pipelines and API services on both CPU and GPU-based infrastructure.
- 5+ 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 in 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.
Annual Salary
$110,000.00 - $300,500.00
The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate / annual salary to be offered to the selected candidate.
Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.
At this time, GEICO will not sponsor a new applicant for employment authorization for this position.
Benefits :
As an Associate, you’ll enjoy our
- to help secure your financial future and preserve your health and well-being, including :
- 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
- Benefits may be different by location. Benefit eligibility requirements vary and may include length of service.
Coverage begins on the date of hire. Must enroll in New Hire Benefits within 30 days of the date of hire for coverage to take effect.