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Machine Learning Scientist

Radiance Technologies, Inc.Ruston, LA

Overview

Schedule
Full-time
Career level
Senior-level
Remote
On-site

Job Description

Radiance Technologies is searching for a talented Research Data Scientist to join the Advanced Cyber Technology Operation in its Scientific and Technical Intelligence Group. This individual will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and will apply machine learning, data mining, and statistical algorithms to provide insights and advance the needs of various stakeholders. This position will particularly focus on application, research, and development of advanced deep-learning architectures. The ability to work under strict project timelines requires a research-oriented individual capable of independent ideation and effective task prioritization. Flexibility and willingness to transition between applications is critical as our mission calls for a wide variety of domains including embedded systems, hardware and software security, remote sensing, modeling and simulation, and scientific computation (biology, thermodynamics, electromagnetics, etc.). Responsibilities will include documentation of technical progress, effective communication within a team, and presentation of results and progress.

Required Skills:

  • Master's Degree in Computer Science, Mathematics, Statistics, Physics, or related area
  • Minimum GPA of 3.5
  • US citizenship with the ability to obtain a security clearance
  • Strong programming background in Python
  • A working knowledge of major Deep-Learning architectures: Multilayer Perceptrons (MLPs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders, and Transformers
  • Experience in applying core Machine Learning methodologies: Regression, Classification, Dimensionality Reduction, Neural Networks & Deep Learning, Feature Engineering, Reinforcement Learning

Desired Qualifications:

  • Possesses or pursuing Ph.D. in Computer Science, Mathematics, Statistics, Physics, or related area
  • Publications/presentations demonstrating strong research experience
  • Experience in an applied quantitative, scientific domain
  • Experience with PyTorch, Pandas, Seaborn, SciPy, or respective 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

Clearance:

Applicants selected may be subject to a government security investigation and must meet eligibility requirements for access to classified information.

Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

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FAQs About Machine Learning Scientist Jobs at Radiance Technologies, Inc.

What is the work location for this position at Radiance Technologies, Inc.?
This job at Radiance Technologies, Inc. is located in Ruston, LA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Radiance Technologies, Inc.?
Employer has not shared pay details for this role.
What employment applies to this position at Radiance Technologies, Inc.?
Radiance Technologies, Inc. lists this role as a Full-time position.
What experience level is required for this role at Radiance Technologies, Inc.?
Radiance Technologies, Inc. is looking for a candidate with "Senior-level" experience level.
What is the process to apply for this position at Radiance Technologies, Inc.?
You can apply for this role at Radiance Technologies, Inc. either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.