← Serch more jobs

Generative AI Engineer

LinkedIn Equifax Atlanta, GA
Mid-Senior level Posted April 3, 2026 Job link
Thinking about this job
Not Met Priorities
What still needs stronger evidence
Requirements
  • 2+ years in shipping production grade software.
  • 1+ years experience in deploying solutions on modern cloud environments.
  • Ability to learn and apply new technologies; passion for staying abreast of the latest advancements in Generative AI research and technology; passion for AI research and a strong desire to contribute to cutting-edge projects
  • Proficiency in Python, LangChain, and either Java or C/ C++
  • Experience with REST API clients and platforms such as Spring/ Flask.
  • Strong communication skills of analytical results to technical and non-technical audiences alike
  • Exposure in Vertex AI, GCP AI/ML services (AutoML, BigQuery ML, Cloud Run, etc.) or a similar cloud technology
  • Strong foundational skills in Linux Operating System.
  • Understanding of NLP, deep learning, and generative architectures (Transformers, Diffusion Models, etc.)
  • Background in credit risk, financial data analytics or risk modeling.
  • Experience working with large datasets on a big data platform (e.g., Google Cloud, AWS, Snowflake, Hadoop)
  • Experience in Business Intelligence, data visualization, and customer insights
  • Familiarity with data governance, model bias mitigation, and regulatory frameworks (GDPR, AI Act, SEC compliance).
  • Experience with MLOps practices, model monitoring, and CI/CD for AI workflows.
  • Knowledge of prompt tuning, fine-tuning, and parameter-efficient methods (LoRA, PEFT).
  • Hands-on experience with RAG, multi-modal AI, and hybrid AI architectures.
Preferred Skills
  • Master’s degree in a related field is a strong plus
  • Exposure in Vertex AI, GCP AI/ML services (AutoML, BigQuery ML, Cloud Run, etc.) or a similar cloud technology
  • Strong foundational skills in Linux Operating System.
  • Understanding of NLP, deep learning, and generative architectures (Transformers, Diffusion Models, etc.)
  • Background in credit risk, financial data analytics or risk modeling.
  • Experience working with large datasets on a big data platform (e.g., Google Cloud, AWS, Snowflake, Hadoop)
  • Experience in Business Intelligence, data visualization, and customer insights
  • generation.
  • Familiarity with data governance, model bias mitigation, and regulatory frameworks (GDPR, AI Act, SEC compliance).
  • Experience with MLOps practices, model monitoring, and CI/CD for AI workflows.
  • Knowledge of prompt tuning, fine-tuning, and parameter-efficient methods (LoRA, PEFT).
  • Hands-on experience with RAG, multi-modal AI, and hybrid AI architectures.
  • Contributions to the AI community through publications, open-source projects, or conference presentations.
Education
  • (Not required) – Bachelor’s degree or higher in Computer Science or Computer Engineering, Statistics, Mathematics, or a related quantitative field
  • (Not required) – Master’s degree in a related field is a strong plus