Oddball is seeking to improve the daily lives of millions of people by bringing quality software to the federal space, specifically by designing, implementing, and maintaining ML solutions that enable secure, scalable, and data-driven decision-making.
Requirements
- Strong hands-on experience with AWS SageMaker for model development and deployment.
- Proficiency with Python and ML libraries such as scikit-learn, TensorFlow, or PyTorch.
- Experience building and maintaining end-to-end ML workflows (training, evaluation, deployment, monitoring).
- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with ETL pipelines and working with large, structured/unstructured datasets.
- Knowledge of cloud-based data environments and distributed computing (AWS, Spark, or similar).
- Awareness of compliance requirements in healthcare/federal settings (HIPAA, NIST, RMF)
Responsibilities
- Develop, train, and deploy machine learning models using AWS SageMaker and related cloud-based services.
- Design and maintain end-to-end ML pipelines for data ingestion, training, testing, deployment, and monitoring.
- Collaborate with data engineers and data scientists to ensure datasets are clean, well-structured, and ready for modeling.
- Implement monitoring, performance tuning, and retraining strategies for production models.
- Document ML workflows, ensuring transparency and compliance with DHA policies.
- Ensure all ML solutions adhere to federal security and privacy frameworks (HIPAA, NIST, CMMC, RMF)
- Support cross-functional initiatives involving predictive analytics, automation, and healthcare decision support.
Other
- Applicants must be authorized to work in the United States.
- In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance.
- Bachelor’s Degree
- Perform other related duties as assigned
- Must be able to work fully remote
