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Radio Frequency Machine Learning System Engineer
2 months ago
We are seeking a highly skilled Radio Frequency Machine Learning System Engineer to join our team at the Naval Sea Systems Command. As a key member of our team, you will be responsible for designing and developing software components and algorithms for the integration and creation of required capabilities and characterizing system performance.
Key Responsibilities- Provide technical expertise in the development and design of various software components and algorithms for the integration and creation of required capabilities and characterizing system performance.
- Develop and implement Machine Learning models and algorithms for automation, Radio Frequency (RF) signal analysis, and Software Defined Radio (SDR) control.
- Leverage advanced technical knowledge of data science, machine learning, and related techniques to write software in support of systems used for RF signal collection and analysis.
- Provide expert mathematical analysis and programming support in the design and development of secure systems and applications.
- Provide proactive technical leadership for software development activities across several critical programs, continuous improvement of the organization's systems development process.
- Work closely with contractors on technical issues, including defining technical requirements and monitoring technical performance.
- Ensure that contractors deliver critical capabilities to keep programs on schedule and meet customer needs.
- Participate in analysis of new vendor capability and ongoing vendor evaluations.
- Work closely with sponsors, the fleet, laboratories and contractors.
- Must be a US Citizen.
- Must be determined suitable for federal employment.
- Must participate in the direct deposit pay program.
- New employees to the Department of the Navy will be required to successfully pass the E-Verify employment verification check.
- Within the Department of Defense (DoD), the appointment of retired military members within 180 days immediately following retirement date to a civilian position is subject to the provisions of 5 United States Code 3326.
- Males born after must be registered for Selective Service.
- You will be required to obtain and maintain an interim and/or final Secret security clearance prior to entrance on duty.
- This position is covered under the Defense Acquisition Workforce Improvement Act (DAWIA).
- Certification in the Acquisition Functional Area and category assigned to the position is required within established category timeframes.
- This is a Cyberspace Workforce position, work role code 441 (Network Operations Specialist), proficiency level Intermediate.
- You will be required to obtain and maintain qualification in DoD Cyber Workforce and Department of Navy policies.
- This position may require travel from normal duty station to CONUS and OCONUS and may include remote or isolated sites.
This is an interdisciplinary position and may be filled by a General Engineer (0801-series), an Electrical Engineer (0850-series), a Computer Engineer (0854-series), an Electronics Engineer (0855-series), or a Computer Scientist (1550-series) depending upon the qualifications of the candidate.
Applicants in positions with occupational series other than those listed (0801, 0850, 0854, 0855 and 1550) may apply; however, you must apply directly to the series listed in this flyer that is most applicable to your qualifications.
Your resume must demonstrate at least one year of specialized experience at or equivalent to the ND-3 pay band (GS-9 through GS-11 equivalency) in the Federal service or equivalent experience in the private or public sector.
Specialized experience must demonstrate the following: As a professional engineer or scientist applying systems engineering principles to design or develop software.
Examples of qualifying experience may include (1) knowledge of and experience with Software Defined Radios (SDR), including programming, designing, configuring, controlling, and data processing; (2) knowledge of and experience with Radio Frequency (RF) digital signal processing techniques, including A/D conversion, FFTs, and filtering techniques; (3) knowledge of and experience with Machine Learning frameworks, techniques, and algorithms; (4) knowledge of and experience with the application of Machine Learning to RF signal detection and classification; (5) experience with multiple software development languages (Python, C++, C#, etc.); (6) familiarity with laboratory prototyping of software and hardware modules, components, and systems.
Additional qualification information can be found from the following Office of Personnel Management website: Occupational Requirements (IOR): All Professional Engineering Positions, 08XX Computer Science Series, 1550.
Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment.
Applicants must meet at least one of the following positive education qualifications requirements of the Office of Personnel Management (OPM) Qualifications Standards Manual:
Professional Engineering Series (08XX) - Degree: A professional engineering degree from an ABET-accredited college or university; OR a degree with curriculum in differential and integral calculus, with additional courses in five of the following seven areas of engineering science or physics: (a) statics, dynamics; (b) strength of materials (stress-strain relationships); (c) fluid mechanics, hydraulics; (d) thermodynamics; (e) electrical fields and circuits; (f) nature and properties of materials (relating particle and aggregate structure to properties); and (g) any other comparable area of fundamental engineering science or physics, such as optics, heat transfer, soil mechanics; or electronics; OR
Professional Engineering Series (08XX) - Substitution of Education/Experience: A combination of education and experience that furnished (1) a thorough knowledge of the physical and mathematical sciences underlying professional engineering; and (2) a good understanding, both theoretical and practical, of the engineering sciences and techniques and their applications to one of the branches of engineering. The adequacy of such background must be demonstrated by one of the following: (a) professional registration, (b) evidence of successfully passing the Engineer-in-Training (EIT) examination; (c) successful completion of at least 60 semester hours of courses in the physical, mathematical, and engineering sciences and in engineering that included the courses specified above; or (d) successful completion of a curriculum leading to a bachelor's degree in engineering technology or in an appropriate professional field, e.g., physics, chemistry, architecture, computer science, mathematics, hydrology, or geology, may be accepted in lieu of a degree in engineering provided that it included at least 1 year of professional engineering experience acquired under professional engineering supervision and guidance.
1550-Computer Science Series: A degree in computer science; or a degree with at least 30 semester hours in a combination of mathematics, statistics, and computer science. At least 15 of these 30 semester hours must have been in a combination of statistics and mathematics that included differential and integral calculus.
You must provide a copy of your college transcripts with your application. See the Required Documents section of this announcement for more information.
