What You’ll Do: As a Signals Engineer, you will provide subject matter expertise in support of the ideation, planning, and execution of research and product initiatives focused on novel signal and data processing for space systems and space domain applications. You will work in tandem with the Engineering, Data Science, and Astrodynamics teams to help transition technologies and capabilities you develop into Slingshot digital engineering products. Slingshot Aerospace cares deeply about our commitment to company values, mission, and purpose. The core competencies we will be looking to identify include: intellectual agility, ability to develop innovative solutions, leadership, performance-orientation, and industry expertise. Position Responsibilities: Develop, test, and validate mathematical models, numerical algorithms, prototypes, simulations, data analysis and data synthesis Learn about and work with a variety of data types, including raw or derived data originating from GNSS receivers, communications systems, radio frequency systems, and other space and ground-based sensing modalities, as well as any related data formats Assist in shaping and refining new and existing products Provide subject matter expertise to the capture teams in the review and evaluation of funding opportunities and the subsequent bid and proposal process Support product demonstrations, business development, customer engagement, and company outreach functions Author or co-author various forms of internal and external reports, presentations and documents, including journal and/or conference papers Attend industry events to present the findings of your work and network with industry leaders Perform other duties as assigned (to be less than 10% of the responsibilities listed above) Pre-Requisites Must be a U.S. citizen eligible for government clearances

Requirements

MS in Electrical Engineering, Aerospace Engineering, Mathematics, or other relevant field, or B.S. degree in related fields with 4+ years of experience in signal processing Experience with signal processing for GNSS, Radar, RF, or other types associated with space-based or supporting ground segment systems Experience with statistical methods for signal and data processing Demonstrated experience in modeling and simulation Proficiency with one or more programming/scripting languages (Python, Java, Kotlin, C++) Proficiency with software version control environments (e.g. git) Strong verbal communication and technical writing skills Comfortable with remote work in a rapidly moving startup environment Preferred Skills Familiarity with algorithms and techniques for detection, estimation, tracking, navigation TS/SCI eligible Experience with machine learning methods Peer-reviewed publications in a related area Demonstrated experience with the application of machine learning and/or artificial intelligence methodologies Demonstrated experience in space domain applications Location: Remote, United States Classification: Full-time Exempt Compensation: $119,110-$198,400 US-based Candidates: we are currently only able to hire residents of the following U.S. states: AL, AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MA, MD, MI, MN, MO, MT, NC, NJ, NM, NV, NY, OH, OK, OR, RI, TN, TX, UT, VA, WA, WI, WV We are unable to consider candidates residing in other U.S. states at this time. Internationally-based Candidates: we are currently only able to hire residents of the following locations: United Kingdom. We are unable to consider candidates residing in other countries at this time. Equity, Diversity & Inclusion are key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, and backgrounds, who share a passion for creating a safer, more connected world. Diversity not only includes race and gender identity, but also national origin, citizenship, sex, color, veteran status, disability, genetic information, or any other protected characteristic that is part of one’s identity. All of our employees’ points of view are key to our success, and we embrace individuality.