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, we 're 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 who are at the forefront of APL's mission to provide innovative solutions to critical challenges. As a Machine Learing Analyst ... You will research, implement and analyze prototype algorithms for various machine learning tasks quantify and document the performance capabilities and limitations of algorithms for specific tasks, as well as provide metrics of robustness and confidence in specific approaches. You will interact with various data types, formats, and structures for algorithm training and testing perform any 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 for the job if you... Hold a Bachelor's degree in Computer Science, Engineering, Math, Physics, Statistics, or a related field. Have at least three years of relevant experience in the machine learning and data science fields. Are fluent in Python with the ability to translate mathematical concepts into well-documented and efficient code. Have experience developing AI/ML research prototypes in code, using one or more of scikit-learn, Tensorflow, PyTorch, or similar machine learning frameworks in Python. Have knowledge of classification, clustering, deep learning, or decision making algorithms. Can effectively communicate ideas and results. Have demonstrated experience in working with version control software like Git. Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship You 'll go above and beyond our minimum requirements if you... Have a Master 's degree in Computer Science, Engineering, Math, Statistics, or a related field. Have at least four years of experience in designing and implementing AI/ML algorithms for a variety of datasets. Are competent in a wide variety of programming languages, including C++, Python, and Java, on both Linux and Windows platforms. Have familiarity with advanced language features such as object-oriented programming is a plus. Have experience using high-performance computing structures like GPUs and CPU clusters. Have work experience with classification, clustering, deep learning, decision making algorithms, or AI explainability. Why work at APL? The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates. At APL, we celebrate our differences and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's 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. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accommodations@jhuapl.edu. Only by ensuring that everyone’s voice is heard are we empowered to be bold, do great things, and make the world a better place. The referenced pay range is based on JHU APL’s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis. Minimum Rate $90,000 Annually Maximum Rate $220,000 Annually