Machine Learning Research Scientist

Johns Hopkins Applied Physics Lab - Laurel, MD

Full-time - Entry Level

Laurel, MD

Professional, Scientific, and Technical Services

About the position

Are you interested in performing cutting-edge applied machine learning research? We seek a research scientist to research, develop, and deploy the latest machine learning (ML) technologies to urgent and challenging problems in defense and healthcare. We are a hardworking and dedicated team of engineers and scientists creating solutions that make AI systems more reliable under ambitious, real-world conditions. We primarily work in computer vision, but are interested in hearing from people with a diverse set of skills, backgrounds, and levels of experience. As a Machine Learning Research Scientist, you will research, develop, and deploy the latest machine learning (ML) technologies to solve urgent and challenging problems in defense and healthcare arenas. You will collaborate with a skilled team of ML research scientists who design, prototype, brainstorm, and explore ways to make ML models fast, performant, robust, and reliable under various data constraints, such as having limited labels or shifted domains. You will write and present ideas, proposals, and research outcomes directly to our sponsors.

Responsibilities

• Research, develop, and deploy machine learning technologies to solve problems in defense and healthcare.
• Collaborate with a team of ML research scientists to design and prototype solutions.
• Explore ways to enhance ML models for performance and reliability under data constraints.
• Write and present research proposals and outcomes to sponsors.

Requirements

• Bachelor's degree in math, statistics, artificial intelligence, machine learning, computer science, or related field.
• Experience with the basic theory of deep neural networks.
• Experience working in deep learning frameworks such as PyTorch, Keras, Darknet, or TensorFlow.
• Comfortable with statistics, linear algebra, calculus, and other mathematical concepts relevant to theoretical machine learning.
• Ability to obtain Interim Secret level security clearance and ultimately a Secret level security clearance.

Nice-to-haves

• Publications at conferences such as NeurIPS, ICML, ICCV/ECCV, ICLR, AAAI, CVPR.
• Experience with computer vision problems such as image classification/object detection.
• Experience with few-shot learning, domain shift, uncertainty estimation, semi-supervised learning, or self-supervised learning.
• Ph.D. or M.S. in math, statistics, artificial intelligence, machine learning, computer science, or related field.
• Active DoD security clearance.

Benefits

• Tuition reimbursement
• Robust education assistance program
• Unparalleled retirement contributions
• Healthy work/life balance