Machine Learning Analyst

Description Do you have demonstrated machine learning experience and want to apply that experience to solving a wide variety of complex problems in this rapidly evolving field? Do you thrive in a collaborative research environment, working alongside an energetic, multidisciplinary team of scientists and engineers? Are you ready to help the US secure and maintain leadership in the development and fielding of AI/ML algorithms for non-kinetic defense systems? If so, were looking for someone like you to join our team at APL! We are seeking a highly motivated Researcher who will contribute to all phases of the machine learning algorithm development process. You will be joining a team of engineers and scientists at the forefront of APLs mission to provide innovative solutions to critical challenges. As a Machine Learning Analyst: You will research, implement, and analyze prototype algorithms for various machine learning tasks, quantify and document their performance capabilities and limitations, and provide metrics of robustness and confidence in specific approaches. You will interact with various data types, formats, and structures for training and testing algorithms, performing data cleaning, normalization, or manipulation as needed. You will create effective visualizations and documentation to explain complex topics to a variety of audiences. Qualifications You meet our minimum qualifications if you: Hold a Bachelors degree in Computer Science, Engineering, Math, Physics, Statistics, or a related field. Have at least three years of relevant experience in machine learning and data science. Are fluent in Python and can translate mathematical concepts into well-documented, efficient code. Have experience developing AI/ML research prototypes using frameworks like scikit-learn, TensorFlow, PyTorch, or similar. Possess knowledge of classification, clustering, deep learning, or decision-making algorithms. Can effectively communicate ideas and results. Have experience with version control software like Git. Can obtain an Interim Secret security clearance and ultimately a Secret clearance; U.S. citizenship required. Additional qualifications: Masters degree in related fields. At least four years of experience designing and implementing AI/ML algorithms. Proficiency in programming languages including C++, Python, and Java on Linux and Windows. Familiarity with object-oriented programming and high-performance computing structures like GPUs and CPU clusters. Experience with classification, clustering, deep learning, decision algorithms, or AI explainability. Why work at APL? The Johns Hopkins University Applied Physics Laboratory (APL) offers a vibrant, inclusive environment where you can grow professionally, contribute to critical national security projects, and collaborate with inspiring teammates. We provide excellent benefits, including education assistance, retirement contributions, and a healthy work/life balance. Our campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at http://www.jhuapl.edu/careers. About Us APL is an Equal Opportunity/Affirmative Action employer. We value diversity and are committed to providing accommodations to individuals with disabilities during the hiring process. All qualified applicants will receive consideration regardless of race, creed, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or other protected characteristics. The pay range for this position is from $90,000 to $230,000 annually, based on experience and qualifications. We offer comprehensive benefits, including retirement plans, paid time off, medical/dental/vision insurance, life insurance, disability coverage, flexible spending accounts, and training opportunities. Applications are accepted on a rolling basis. Position Details: Minimum Rate: $90,000 annually Maximum Rate: $230,000 annually Company:

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Senior (5+ years of experience) Tagged as: Academia, Classification, Clustering, Machine Learning, NLP, United States #J-18808-Ljbffr