Northeastern University-posted 3 months ago
$112,180 - $162,662/Yr
Full-time • Senior
Portland, ME

This is a 1-year fixed term position. The Senior Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University's Experiential AI Institute, will lead the development and delivery of AI solutions across diverse industries. The role involves building end-to-end AI pipelines—from business problem scoping to deployment and monitoring of production-grade models—with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and brings a strong combination of academic and industry experience. They will possess deep, hands-on expertise in modern AI architectures including convolutional neural networks, transformers, and diffusion models. The role also requires significant experience in classical machine learning methods such as decision trees, gradient boosting machines, and both shallow and deep learning networks. A demonstrated ability to interface with clients to gather requirements, communicate insights, and lead solution design are essential. A successful candidate will also demonstrate mentoring experience and a strong track record of translating complex business needs into scalable AI solutions. Experience in the consulting industry is preferred.

  • Lead the development and delivery of AI solutions across diverse industries.
  • Build end-to-end AI pipelines from business problem scoping to deployment and monitoring of production-grade models.
  • Interface with clients to gather requirements and communicate insights.
  • Mentor junior staff and foster a culture of technical excellence.
  • Translate complex business needs into scalable AI solutions.
  • Ph.D. (strongly preferred) or Master’s degree in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field, with a focus on Deep Learning or Generative AI.
  • Minimum of 5 years of industry experience in designing, developing, and deploying AI/ML solutions.
  • Demonstrated academic and industrial contributions in Generative AI and Deep Learning.
  • Proven experience building AI solutions using classical ML algorithms such as decision trees and gradient boosting machines.
  • Demonstrated client-facing experience, including engagement scoping and expectation management.
  • Hands-on experience with distributed data processing (e.g., Apache Spark, Hadoop).
  • Track record of building and scaling ML pipelines for both structured and unstructured data.
  • Proven record of technical leadership in architecture and delivery of robust and scalable AI systems.
  • At least 3 years of MLOps experience, including deployment and monitoring of AI models.
  • Familiarity with containerization (Docker) and orchestration tools (Kubernetes).
  • Medical, vision, and dental insurance.
  • Paid time off.
  • Tuition assistance.
  • Wellness and life benefits.
  • Retirement benefits including 401k.
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