AI/ML Engineer (Mid–Senior Level)

Atlanta, GA

Hybrid role

$75 per hour (Contract-to-Hire or Full-Time)

ABOUT THE ROLE

Join our AI Platform & Data Innovation team as a Mid–Senior Level AI/ML Engineer in Atlanta, GA (hybrid). In this role, you will help expand and optimize our enterprise AI Platform, accelerating how teams build, deploy, and scale machine learning solutions across risk, fraud, identity, credit decisioning, and internal automation use cases. You will work hands-on with ML engineering, LLM/agentic system integration, model deployment, and platform development within a modern cloud environment. This position is ideal for engineers passionate about enabling data scientists, MLOps teams, and product groups to deliver models faster, more reliably, and with high governance. You will collaborate cross-functionally, mentor junior team members, and contribute to best practices, with a preference for candidates experienced in cloud environments, containerization, and regulated data domains.

WHAT YOU'LL DO

• Build, train, and optimize ML/LLM models for risk scoring, fraud detection, identity verification, customer insights, and automated decisioning
• Fine-tune foundation models (OpenAI, Anthropic, Google, HuggingFace) for company-specific data and use cases
• Develop retrieval-augmented generation (RAG) pipelines, agentic workflows, and prompt-engineering strategies
• Design and improve enterprise AI platform components, including model training pipelines, feature stores, vector databases, deployment orchestration, and monitoring tools
• Build reusable frameworks, SDKs, and internal tooling to operationalize AI solutions at scale
• Package and deploy models into production using CI/CD and containerized environments (Docker, Kubernetes, Argo, MLflow, SageMaker, Databricks, or internal tools)
• Implement model governance, monitoring, and performance evaluation aligned to regulatory and compliance standards
• Create automated testing frameworks for data quality, drift detection, and model validation
• Collaborate with data scientists, product managers, risk leaders, and platform architects to translate requirements into scalable AI components
• Participate in architecture reviews, design sessions, and Agile ceremonies
• Mentor junior team members and contribute to internal best practices and standards

WHAT YOU BRING

• 4–7+ years of experience in AI/ML engineering, machine learning, or applied data science
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-Learn, HuggingFace Transformers)
• Hands-on experience developing and deploying ML/LLM models into production environments
• Experience with cloud platforms (AWS preferred), containerization (Docker, Kubernetes), and distributed compute
• Practical knowledge of vector databases (Pinecone, Milvus, FAISS), RAG patterns, and LLM fine-tuning
• Solid understanding of MLOps tools & workflows (MLflow, SageMaker, Databricks, Kubeflow, Airflow, etc.)
• Familiarity with secure data pipelines, model governance, and compliance frameworks
• Experience supporting or building enterprise-scale AI platforms or ML feature stores (preferred)
• Background in financial services, credit, risk, fraud, or regulated data environments (preferred)
• Exposure to reinforcement learning, agentic systems, or multi-model orchestration frameworks (preferred)
• Experience with large, complex datasets in Snowflake or other cloud data warehouses (preferred)
• Strong communication skills and ability to translate technical concepts into business value