Project Manager Design - DPW-Design
City of Indianapolis
RecentPosted Mar 12
✓ Fresh Listing
Posted: March 19, 2026 (0 days ago)
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ENGINEER/SCIENTIST
Naval Sea Systems Command
Department of the Navy
Location
Salary
$125,776 - $192,331
per year
Type
Full-Time
More Engineering jobs →Closes
March 30, 2026More Navy jobs →
GS-14 Pay Grade
Base salary range: $104,604 - $135,987
Typical requirements: 1 year specialized experience at GS-13. Senior expert or supervisor.
Note: Actual salary includes locality pay (15-40%+ depending on location).
Job Description
Summary
This job involves working as a senior engineer or scientist in the Navy's research center, focusing on using advanced machine learning and data analysis to improve electronic warfare systems against modern threats like radars and jamming.
You'll advise teams, develop strategies for implementing these technologies in real-world systems, and provide expert support on how to design, test, and upgrade them.
It's a great fit for experienced professionals with a strong background in engineering or science who enjoy tackling complex defense challenges and have knowledge of radio frequency technologies.
Key Requirements
- At least one year of specialized experience at GS-12/13 level or equivalent, providing technical direction in warfare system design and implementation
- Expertise in deep machine learning and big data analysis
- Knowledge of real-time learning algorithms and predictive models for countering radars, communications, jamming, and electronic protection techniques
- Strong understanding of conventional RF/EW theory and practice
- Ability to advise on strategies for specifying, contracting, testing, supporting, and improving machine learning in deployed EW systems
- Qualifications in professional engineering (0801), general physical science (1301), mathematics/statistics (1501), operations research (1515), or computer science (1550) series
Full Job Description
You will serve as an ENGINEER/SCIENTIST in the Rapid Mission Integration & Interoperability Department (MX), Advanced EMSO Applied Research & Rapid Capabilities Division (MXN), Advanced Concepts Group Branch (MXNL) of NAVAL SURFACE WARFARE CENTER.
This position is part of the Warfare Centers Personnel Demonstration Project. The ND-05 pay band encompasses positions equivalent to the GS-14 and GS-15.
Your resume must demonstrate at least one year of specialized experience at or equivalent to the ND-04 (GS-12/13 equivalent) grade level or pay band 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 providing technical direction in the design and implementation of warfare system capabilities for the advancement of an organization.
Additional qualification information can be found from the following Office of Personnel Management website: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/#url=List-by-Occupational-Series AND https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/0800/files/all-professional-engineering-positions-0800.pdf FOR 0801: Professional Engineering Series FOR 1301: General Physical Science FOR 1501: General Mathematics and Statistics Series FOR 1515: Operations Research Series FOR 1550: Computer Science Series 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. Major Duties:
- You will serve as a senior team member and advisor in the area of Deep Machine Learning and Big Data Analysis.
- You will provide in-depth technical support to the EMW and the Advanced EMSO Applied Research and Rapid Capabilities Division.
- You will provide the needed technical expertise for the application of real-time learning algorithms and predictive models to counter modern and more agile radars, communications, jamming, and EP techniques.
- You will speak authoritatively on the strategy for implementing machine learning algorithms to deployed EW systems including how they will be specified, contracted for, tested, supported, improved, and more
- You will be well versed in both conventional RF/EW theory and practice in order to understand the problems to be solved.
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