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AI/ML Engineer - Finance Hybrid - Mayo Clinic
ML Engineer
Develop and deploy advanced time‑series and generative AI models for finance applications, leveraging Python, deep‑learning frameworks, and cloud services while collaborating with cross‑functional teams in a hybrid environment.
About the role
Key Responsibilities
- Design, build, and productionize time‑series forecasting and generative AI models for financial and accounting use cases.
- Collaborate with data engineers, finance analysts, and domain experts to translate business requirements into scalable ML solutions.
- Implement end‑to‑end pipelines using Python, TensorFlow/PyTorch, and cloud services (AWS) for data ingestion, model training, validation, and deployment.
- Monitor model performance in production, conduct root‑cause analysis, and iterate to improve accuracy and reliability.
- Stay current with emerging AI/ML research and integrate state‑of‑the‑art techniques into finance‑focused solutions.
Requirements
- Bachelor’s or higher in Computer Science, Engineering, Mathematics, or related field with 3+ years of hands‑on ML engineering experience.
- Proficiency in Python and deep‑learning frameworks such as TensorFlow or PyTorch.
- Strong background in time‑series analytics, statistical modeling, and generative AI techniques.
- Experience deploying ML models on AWS (SageMaker, Lambda, EC2, or similar) and managing CI/CD pipelines.
- Excellent problem‑solving skills and ability to work collaboratively in a hybrid, multidisciplinary environment.
Skills
pythontensorflowpytorchgenerative aiaws