Dana-Farber Cancer Institute is looking to solve the problem of building reusable and scalable AI/ML tools and pipelines to support operations, research, and clinical practice.
Requirements
- 3 years of work experience in machine learning and AI required.
- Experience with machine learning, NLP, and computer vision.
- Experience with cloud infrastructure, data engineering, and data labeling.
- Experience with CI/CD pipelines and cloud environments.
- Experience with batch, online, streaming, and edge training/inference.
- Knowledge of best-in-class data solutions and machine learning models.
- Experience with GUI designs, user interviews, and end-to-end testing.
Responsibilities
- Plan, advise and execute on scalable practices for development, deployment, and long-term monitoring for AI solutions, ensuring a delivery that is built for scale, reliable telemetry tracking, informative monitoring and diagnosis of model drift, and cross-platform efficiency.
- Implement and maintain best-in-class data solutions, managing machine learning models from deployment to retirement, ensuring models are well organized, auditable, and continuously perform with the highest degree of accuracy.
- Develop CI/CD pipelines for models in cloud environments, including batch, online, streaming, and edge training/inference.
- Elicit functional requirements from end users and data science teams, utilizing methods such as user interviews, mockups, wireframes, end-to-end testing, prototypes, GUI designs, and use cases.
- Communicate status on various project/program efforts to multiple groups including the AIOS team, client-facing leads, project sponsors, business owners, and internal stakeholders.
- Mentor and provide guidance to junior and new team members.
- Develop and maintain AI/ML tools and pipelines to support Dana-Farber operations, research, and clinical practice.
Other
- Bachelor’s degree in a related field (Computer Science, Data Science, Engineering) required.
- Master’s degree preferred.
- Ability to work in a matrixed team environment and collaborate with client-facing leads, software engineers, product managers, project managers, project sponsors, and clients.
- Ability to communicate status on various project/program efforts to multiple groups.
- Ability to mentor and provide guidance to junior and new team members.
