Machine Learning Engineer - Remote

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