Responsibilities
- Design and develop AI-enabled solutions that support API development and modernization.
- Implement AI-driven code generation, code review, and documentation automation.
- Support automated language conversion from legacy COBOL to modern programming languages.
- Develop APIs that support AI and machine learning workflows, including model deployment and inference.
- Build and deploy machine learning models using Python and modern ML frameworks.
- Support MLOps practices including model versioning, monitoring, and retraining.
- Collaborate with full stack and data engineers to integrate AI capabilities into APIs.
- Contribute to testing, validation, and performance evaluation of AI-enabled services.
- Demonstrated ability/evidence of high volume of accurate code production.
- Competency in Openshift Serverless, AWS Serverless, Kubernetes, GitHub, and JIRA.
Basic qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, or related field, or equivalent experience.
- 3 to 5 or more years of experience in software engineering or machine learning engineering.
- Strong proficiency in Python.
- Experience with machine learning frameworks such as PyTorch or TensorFlow.
- Experience deploying models into production environments using APIs.
- Familiarity with cloud-based AI platforms and containerized deployments.
- Strong communication abilities.
Preferred qualifications
- Experience with large language models and natural language processing.
- Experience with automated language conversion or legacy modernization.
- Familiarity with FastAPI, model serving frameworks, or MLOps tools.
- Experience supporting regulated or federal environments.
- Ability to contribute to growth & business development activity as necessary.
Tags & focus areas
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