R&D Machine Learning Engineer (Engineering Scientist Associate)

The University of Texas at Austin, a prestigious public research institution, is seeking a R&D Machine Learning Engineer to join their Applied Research Laboratories. This role presents an exciting opportunity to work at the intersection of machine learning and underwater acoustics, developing cutting-edge algorithms for sonar applications.

The position offers a competitive salary range of $88,500-$120,000+ and comes with comprehensive benefits including medical coverage, retirement contributions, and paid time off. Located at the PICKLE RESEARCH CAMPUS in Austin, TX, this full-time role combines the stability of academia with the innovation of advanced research.

As an R&D Machine Learning Engineer, you'll be responsible for developing novel machine learning algorithms, conducting sophisticated data analysis of acoustic systems, and coordinating with implementation teams. The role requires expertise in Python programming and machine learning, with opportunities to work on high-performance computing and applied statistics projects.

The ideal candidate will have a bachelor's degree in a technical field, though an advanced degree is preferred. Strong programming skills in Python or C++ are essential, along with knowledge in areas such as machine learning, data pipelining, or robotics. The position requires US citizenship and ability to obtain security clearance due to the nature of the work.

Working at UT Austin offers unique advantages: you'll be part of a leading research institution that's consistently ranked among Forbes's top employers. The university provides a collaborative environment where you can contribute to meaningful research while enjoying excellent benefits and work-life balance. The role offers opportunities for professional growth through research presentation, travel for data collection, and work with cutting-edge technologies.

This position would be ideal for someone who combines technical expertise with a passion for research and innovation, and who wants to apply machine learning techniques to solve complex real-world problems in underwater acoustics. The stable institutional setting, competitive compensation, and opportunity to work on advanced technical challenges make this an attractive position for qualified candidates.