CSAA Insurance Group, a AAA insurer, is one of the leading personal lines property and casualty insurance groups in the United States. They are seeking a skilled AI/ML Engineer to contribute to the design, implementation, and support of AI and ML capabilities within their Data & AI Platform Engineering team.

Responsibilities:

Design, implement, and support AI and ML components under the guidance of senior engineers and architects
Build AI/ML solutions that are secure, stable, testable, and maintainable, following established platform and engineering patterns
Apply existing engineering and AI/ML frameworks to ensure consistency, scalability, and operational readiness
Evaluate tradeoffs between performance, scalability, cost, and usability when implementing solutions
Implement pipelines to ingest, process, and enrich unstructured and semi-structured data such as documents and text
Work with metadata, embeddings, and semantic representations to improve search, retrieval, and downstream AI use cases
Apply semantic modeling techniques to help make data more discoverable, interpretable, and useful to end users and applications
Write high-quality, production-grade code using modern software engineering best practices
Contribute to automated testing, code reviews, and CI/CD pipelines for AI/ML systems
Turn well-defined designs into working software and deliver on commitments reliably
Implement solutions to moderately complex problems by understanding requirements, constraints, and business context
Collaborate with data scientists, platform engineers, and business partners to deliver effective AI/ML capabilities
Contribute to user stories, technical documentation, and design discussions
Support MLOps / FMOps practices such as model deployment, versioning, monitoring, and troubleshooting
Identify operational issues and work with the team to improve reliability, observability, and maintainability
Contribute improvements to existing pipelines, tools, and platform components
Apply LLMs and prompt engineering techniques to business use cases under established architectural and governance guidelines
Contribute to solutions using managed model platforms such as AWS Bedrock
Assist in evaluating and integrating new AI capabilities into the platform
Build AI/ML solutions that adhere to data and AI governance standards, including documentation, lineage, and testing requirements
Partner with governance and compliance teams to ensure AI/ML implementations meet enterprise expectations
Follow established practices for model versioning, validation, and transparency

Requirements:

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field
3+ years of experience in AI/ML engineering or applied machine learning
Experience delivering AI/ML solutions that are used in production environments
Hands-on experience working with unstructured data, embeddings, or semantic techniques
Strong programming skills, particularly in Python; experience with Java or similar languages is a plus
Experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
Experience deploying AI/ML workloads on cloud platforms, preferably AWS and AWS Bedrock
Experience with data processing technologies such as Spark, SQL, or NoSQL systems
Familiarity with Palantir (Foundry, AIP, or related tools) is required
Exposure to MLOps/FMOps practices and governed AI environments
Strong problem-solving and analytical skills with attention to detail
Effective communication and collaboration skills in cross-functional teams
Ability to operate in an agile, fast-paced engineering environment
Desire to learn, grow, and deepen expertise in AI/ML engineering and platform development
Actively shapes our company culture (e.g., participating in employee resource groups, volunteering, etc.)
Lives into cultural norms (e.g., willing to have cameras when it matters: helping onboard new team members, building relationships, etc.)
Travels as needed for role, including divisional / team meetings and other in-person meetings
Fulfills business needs, which may include investing extra time, helping other teams, etc

Senior Machine Learning Engineer – Ranking

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