Machine Learning Research Scientist
About The Position
Radiance Technologies is seeking a Research Data Scientist to join the Advanced Cyber Technology Operation within its Scientific and Technical Intelligence Group. The role provides expertise in data analytics and algorithm development to support the integration and analysis of diverse data sources. The scientist will apply machine learning, data mining, and statistical algorithms to generate insights and address stakeholder needs, with a particular focus on applying, researching, and developing advanced deep-learning architectures. The position requires a research-oriented individual who can work under strict project timelines, develop ideas independently, and prioritize tasks effectively. Flexibility in transitioning among applications is important; mission areas may include embedded systems, hardware and software security, remote sensing, modeling and simulation, and scientific computation in areas such as biology, thermodynamics, and electromagnetics. Responsibilities also include documenting technical progress, communicating effectively within a team, and presenting results and progress.
Requirements
- Master's degree in Computer Science, Mathematics, Statistics, Physics, or a related area.
- Minimum GPA of 3.5.
- U.S. citizenship and ability to obtain a security clearance.
- Strong programming background in Python.
- Working knowledge of Multilayer Perceptrons (MLPs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders, and Transformers.
- Experience applying core machine-learning methodologies, including regression, classification, dimensionality reduction, neural networks and deep learning, feature engineering, and reinforcement learning.
Nice To Haves
- Possesses or is pursuing a Ph.D. in Computer Science, Mathematics, Statistics, Physics, or a related area.
- Publications or presentations demonstrating strong research experience.
- Experience in an applied quantitative or scientific domain.
- Experience with PyTorch, Pandas, Seaborn, SciPy, or similar libraries.
- Experience with Git and modern DevSecOps practices.
- Experience with modern MLOps frameworks such as ClearML.
- Strong programming background in C++.
- Experience with numerical and computational methods.
- Knowledge of differential equations.
- Knowledge of algorithm analysis and computing theory.
- Knowledge of graph theory.
Responsibilities
- Provide expertise in data analytics and algorithm development for integrating and analyzing diverse data sources.
- Apply machine learning, data mining, and statistical algorithms to generate insights and advance stakeholder needs.
- Apply, research, and develop advanced deep-learning architectures.
- Work independently, prioritize tasks, and meet strict project timelines.
- Transition between applications and mission domains as needed.
- Document technical progress.
- Communicate effectively within a team.
- Present results and progress.
