Applied AI Engineer
$121,624–$217,710 year
Hybrid · San Diego, California, United States
Job Summary
Applied AI Engineer focused on developing, deploying, and maintaining generative AI solutions for insurance products and internal workflows. Responsibilities include end-to-end model fine-tuning, production deployment, monitoring, and optimization; collaborating with cloud engineering, AI, and ML Ops teams to operationalize AI workloads on AWS (SageMaker, Lambda, ECS/EKS, S3); building and maintaining AI/ML pipelines with Snowflake for feature engineering and data preprocessing; adhering to security/compliance standards; documenting models and processes; supporting senior engineers in architecture reviews and operationalization planning; and researching new generative AI technologies. Skills emphasized include proficiency in Python, PyTorch/TensorFlow/Hugging Face, MLOps practices, containerization (Docker/Kubernetes), Snowflake, and strong collaboration and troubleshooting capabilities.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related technical discipline
- 3+ years of experience in AI/ML engineering, with at least 1–2 years focused on generative AI or large language models
- Hands-on experience deploying AI/ML models in cloud environments, preferably AWS
- Familiarity with Snowflake for AI/ML feature engineering and data integration
- Experience in regulated industries or highly data-sensitive environments is a plus
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