AI Systems Engineer: Data Pipelines & Enterprise ML

Northeastern University; Boston (MA); On-site; USD 88,000 - 124,000; Full time

Benefits offered by this job

Tuition assistance

Medical/dental/vision benefits

Wellness program

Job summary

Northeastern University is seeking an Associate AI Engineer to design and implement AI-powered solutions across university operations. You will build robust data pipelines, develop and deploy ML models, and integrate AI capabilities with existing systems to improve efficiency and service quality.

Applicants should have 4–6 years of AI/ML experience, strong Python expertise, and experience with NLP, LLMs, and cloud deployments.

Qualifications

• Bachelor's degree in Linguistics, Computational Linguistics, Computer Science, or related field.
• 4–6 years of experience in AI/ML in production enterprise apps.
• Experience in higher education or similar complex environments preferred.
• Deep understanding of LLM capabilities, prompts, and enterprise interaction patterns.

Responsibilities

• Design, develop, and implement AI solutions to automate university operations.
• Build end-to-end data pipelines and robust ETL processes with Airflow and data warehouses.
• Develop and fine-tune ML models including prompt engineering and domain adaptation.
• Integrate AI systems with existing university infrastructure and monitor production deployments.

Skills

LLM expertise

AI/ML development

Software engineering

Data pipeline engineering

Machine learning engineering

NLP

Cloud computing

System integration

Performance optimization

Security awareness

Data science

AI ethics & governance

Education

Bachelor's degree in related field (CS/Computing/Computational Linguistics)

Tools

Python

TensorFlow/PyTorch

Airflow

CI/CD

Cloud services

Job description

Northeastern University is seeking an Associate AI Engineer to design and implement AI-powered solutions across university operations. You will build robust data pipelines, develop and deploy ML models, and integrate AI capabilities with existing systems to improve efficiency and service quality.

Applicants should have 4–6 years of AI/ML experience, strong Python expertise, and experience with NLP, LLMs, and cloud deployments.