Research Fellow - Artificial Intelligence/Machine LearningUMass Amherst • United States
Research Fellow - Artificial Intelligence/Machine Learning
UMass Amherst
- United States
- United States
Über
Research Fellow - AI/ML Executive Area:
Academic Affairs College/School/MBU:
College of Information & Computer Sciences Department:
Computer Science Work Location:
Amherst Schedule: Full Time Work Arrangement: Onsite Job Summary The Center for Data Science and Artificial Intelligence (CDSAI) in the Manning College of Information and Computer Sciences (CICS) is seeking a Research Fellow to join our applied AI and machine learning team. In this role, you will design, develop, and deploy machine learning and AI solutions that support research initiatives across the university and partner institutions. You will work on technical projects from concept to production, implement best practices, and bridge cutting-edge AI research with practical, scalable applications. You will work closely with researchers, faculty, and external stakeholders to transform complex requirements into robust, deployed ML systems. Essential Functions Design, develop, and deploy machine learning and deep learning models for applied research projects.
Manage multiple concurrent projects, ensuring timely delivery and alignment with stakeholder needs.
Build and maintain MLOps pipelines for model training, evaluation, versioning, and deployment.
Implement scalable ML infrastructure across cloud platforms (e.g., AWS, GCP, Azure) and on-premises environments.
Develop APIs and integration layers to embed ML capabilities into applications and research workflows.
Collaborate with researchers and non-technical stakeholders to translate research questions into technical solutions.
Document technical implementations, model architectures, and research methodologies to ensure reproducibility.
Stay current with emerging AI/ML techniques and evaluate their applicability to Center projects. Other Functions Other duties as assigned. Minimum Qualifications Bachelor's degree or higher in Computer Science, Data Science, Machine Learning, or a related field.
Strong programming expertise in Python, with experience in ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Demonstrated experience deploying ML models to production environments.
Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, DVC, Docker, CI/CD for ML).
Experience with cloud-based ML services and infrastructure (e.g., AWS SageMaker, GCP Vertex AI, Azure ML).
Ability to manage multiple projects and guide junior engineers or collaborators.
Excellent written and verbal communication skills for working with technical and non-technical stakeholders.
Demonstrated ability to work independently and solve complex technical challenges. Preferred Qualifications Experience with LLMs, generative AI, and prompt engineering.
Familiarity with NLP, computer vision, or time-series modeling.
Experience with distributed computing frameworks (e.g., Spark, Ray, Dask).
Background in data engineering and pipeline orchestration (e.g., Airflow, Prefect).
Prior experience in academic or research-focused settings.
Experience mentoring or leading technical teams.
Familiarity with responsible AI practices and model interpretability. Working Conditions Work is performed in a standard office or indoor university environment and involves minimal physical exertion. Work Schedule and Work Arrangement Typical office hours between 8:00 AM and 5:00 PM. Salary Information The salary range is $70,000-$110,000, commensurate with experience and qualifications. Special Instructions for Applicants Alongside your application, please include CV or resume detailing your academic and professional background, a cover letter describing your relevant experience and research interests, and the contact information for three (3) professional references. This position will remain open for the time period required by any applicable collective bargaining agreement and will continue until a suitable candidate pool is identified. Interested applicants are strongly encouraged to apply early.
Sprachkenntnisse
- English
Hinweis für Nutzer
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