AI Engineer

NBME•Philadelphia, PA

1d•Remote

About The Position

NBME is seeking a highly skilled AI Engineer to join our team and take ownership of building, maintaining, and scaling AI-driven systems. This role is critical for translating research innovations into production-ready pipelines and tools that support multiple programs, products, and services. The AI Engineer will work closely with research, IT, and product teams to operationalize AI solutions, ensuring they are reliable, secure, and optimized for performance. This role has been designated as primarily remote, meaning it requires little to no onsite attendance. While this role can be designated as remote, you are offered the flexibility to select if you prefer to work primarily remotely, hybrid, or onsite. At NBME, we continue to innovate and improve how we fulfill the evolving needs of the healthcare community. This commitment starts and ends with the people at NBME. By recruiting and empowering talented individuals from various disciplines and backgrounds, which includes professionals with diverse life experiences, abilities, and perspectives, NBME can take a well-informed, robust approach to advancing medical education and assessment for years to come.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
A minimum of 3 years of experience in AI/ML engineering, including model deployment, MLOps, system monitoring, and production pipelines.
Proficiency with Python and AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Familiarity with vector databases, embeddings, and large-scale NLP applications.
Strong problem-solving skills and ability to work collaboratively in a cross-functional team.
Excellent communication skills for technical and non-technical stakeholders.

Nice To Haves

Experience in educational assessment or healthcare-related AI applications.
Experience with Agentic LLM architectures for complex task completion.

Responsibilities

Design, implement, and maintain production-grade AI and NLP pipelines, including model training, deployment, monitoring, and updates.
Collaborate with research teams on pre-production research and to operationalize prototypes, ensuring reproducibility, scalability, and robustness.
Build and maintain infrastructure for embeddings, large language models, and other AI assets.
Optimize AI systems for performance, reliability, and cost-efficiency.
Implement and maintain monitoring, logging, and alerting for AI systems in production.
Ensure compliance with data security, privacy, and organizational standards.
Support multiple product teams by providing AI engineering expertise, tools, and best practices.
Contribute to technical documentation, knowledge sharing, and internal training initiatives.