What are the responsibilities and job description for the Machine Learning Engineer position at AAA Life Insurance Company?
Overview
Why AAA Life
AAA Life is a respected and trusted American brand that has been focusing on Life Insurance and Annuity Products since 1969. At AAA Life we have over 1.8 million policies where we take pride in earning the trust of our policyholders who understand our promise to be there for them – and their families – when we’re needed most. By joining the AAA Life team, you are joining a company that genuinely cares about helping each other, with a devotion to protect the lives of those around us. We embrace a diverse, equitable, inclusive culture where all associates can feel a sense of belonging and use their unique talents and perspective to influence, innovate, motivate, and thrive.
At AAA Life, we are building a future-focused team using AI and automation to transform life insurance operations. If you're driven by meaningful work and want to deliver solutions that matter to millions of members, this is your opportunity.
How You’ll Work
Work Solution: Hybrid (Tuesday- Thursday)
Relocation Eligibility: Available
Responsibilities
What You’ll Do
We are seeking a highly motivated and technically skilled Machine Learning Engineer to join our Automation and AI team. This role requires strong machine learning and data science expertise, excellent coding practices, and the ability to translate real-world business challenges into impactful AI solutions. While operating within the core values and operating principles of the organization. The ideal candidate is a hands-on contributor who thrives in a fast-paced, purpose-driven environment.
- Design and implement intelligent systems using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to enhance operational efficiency and decision-making.
- Develop AI agents that assist internal teams (e.g., Claims, Underwriting, Member Services) with tasks like summarization, document processing, and knowledge retrieval.
- Partner with strategic vendors and platform providers to explore and integrate enterprise-grade GenAI capabilities into AAA Life’s ecosystem.
- Translate business problems into practical AI solutions, leveraging internal data and LLMs to create scalable tools.
- Implement and refine MLOps practices to support the deployment and monitoring of AI agents and services.
- Collaborate with stakeholders across operations, IT, and automation to align AI initiatives with business goals.
- Mentor junior engineers and advocate for best practices in responsible, sustainable AI implementation.
Qualifications
Qualifications
Basic Required Qualifications
- Bachelor’s degree in a quantitative discipline (Computer Science, Mathematics, etc.).
- 1-3 years of experience working in a data science or ML engineering role.
- Understanding of basic MLOps principles and software engineering best practices.
Preferred Qualifications
- Industry knowledge/experience in finance or insurance.
Position Success Criteria
- Strong proficiency in Python and familiarity with machine learning frameworks.
- Ability to perform data wrangling, exploratory analysis, and model validation.
- Clearly and effectively communicate complex ideas across multiple teams and varying levels of technical understanding.
Essential Job Functions
While performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel, talk, hear and concentrate. Specific vision abilities required by this job include close vision, distance vision, depth perception, and ability to adjust focus.
This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements. Reasonable accommodation will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.
We are committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of an applicant's race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, marital status, genetic information, protected veteran status, or any other status protected by law.