Sr Systems Engineer I (117049BR)

  • Raytheon
  • Tewksbury, Massachusetts, United States
  • 07/02/2018
Secret Engineering - Hardware / Software

Job Description

Location: Tewksbury Massachusetts Security Clearance: Secret

Raytheon Integrated Defense Systems conducts 25 Billion USD per-year in sales, but what attracts brilliant minds to Raytheon is the extraordinary technology and tremendous job satisfaction that comes from making our nation safe. Raytheon is pioneering a push to marry machine learning and advanced algorithm development opportunities together with radar system concepts, in order to increase the effectiveness and capabilities of military systems.

Raytheon Integrated Defense Systems is looking for top candidates to perform the duties of a Senior Systems Engineer to support the Systems Architecture Design and Integration Directorate (SADID). The team member will work with one of the premier radar systems in the world, building advanced algorithms focused on applying state of the art machine learning approaches to a variety of detection, classification, and tracking challenges involving multiple targets in highly complex environments. The individual will collaborate with a team to develop radar system concepts, generate requirements, create models, analyze, and optimize system performance. Furthermore, SADID provides opportunities to invent new concepts and explore ideas relating to defense and the exploration of truly novel capabilities. These Independent Research and Development (IRAD) projects provide the rewards of exploring new research and turning it into real capability for our warfighters.

SADID is the central focus for Mission Systems Integration activities within IDS and we welcome you to join our tradition of achieving excellence through individual thought and team work while leveraging diversity. SADID provides requirements definition and design at the system, subsystem and component level every day in a collaborative environment that is characterized by respect for the individual, problem solving in a team setting, consensus-oriented solutions, and results based recognition. Supporting this mission are teams providing domain expertise and creative solutions in surveillance, naval and missile defense based radar system design, sonar and undersea sensor system design, integrated air and missile defense systems engineering, command and control/battle management system design, combat system and platform architecture design and integration, operational analysis and simulation modeling research and development, software intensive system engineering, cyber solutions and algorithm development for signal processing, tracking and discrimination systems.

Raytheon benefits include: Holiday time, Paid time off (PTO), Flexible Schedules (9/80, Modified Time, Part-time), 401K, Retirement Income Savings, Employee Discounts, Performance Sharing, Educational Assistance, Continuous Learning and much more.

Raytheon offers an innovative and inclusive culture; welcoming diversity and collaboration and providing numerous opportunities for career growth, as well as superior benefits.

Job Description:

The Missile Defense and Sensor Solutions Department is seeking engineering professionals to be part of the System Engineering teams for the Woburn, MA, location. The Engineer will support the design and development of world-class Missile Defense programs. Specific tasks include developing radar system concepts, generating and flowing down requirements, modeling and simulating radar behavior, analyzing data, and supporting integration and test activities.

Note: This position can be either a G08 or G09 level based on the candidate’s qualifications as they relate to the position.

Required Skills:

  • Bachelor’s Degree in Engineering, Science, Mathematics or Statistics with minimum of 4(+) years of experience in the field of engineering or a related technical discipline working with Matlab, C/C++, Java, and/or DOORS
  • Understanding of machine learning concepts such as Gaussian Mixture Models, Hidden Markov Models, Support Vector Machines, Dimensionality Reduction, Neural Network Design, and Nonlinear Programming
  • Experience with system level requirements development, documentation and maintenance
  • Experience developing system models, algorithms, test vectors and analysis tools in support of analyzing requirements and performance
  • Detail oriented self-starter who can function independently
  • Good communications skills, with the ability to develop, document, and maintain processes, methods and tools
  • Ability to obtain a DoD Security Clearance
Desired Skills:
  • Masters/Ph.D. Degree in Engineering, Science, or Mathematics with Computer Science/Machine Learning experience
  • High proficiency one or more scientific analysis and prototyping environment such as Matlab or Python with experience using SciPi/NumPy/Pandas/Keras with Tensor Flow
  • Experience configuring and using GPUs for Machine Learning
  • Prior experience with DoD Radar Design and Development Programs
  • Existing DoD Secret Security Clearance
117049

Raytheon is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status.


Headquartered in Tewksbury, Massachusetts, IDS has 32 locations around the world. Its broad portfolio of weapons, sensors and integration systems supports its customer base across multiple mission areas, including air and missile defense systems; missile defense radars; early warning radars; naval ship operating systems; C5ITM products and services; and other advanced technologies. IDS provides affordable, integrated solutions to a broad international and domestic customer base, including the U.S. Missile Defense Agency, the U.S. Armed Forces and the Department of Homeland Security. Algorithms, Computer Science, Data Science, Machine Learning, Systems Engineering, All, Engineering Algorithms, Computer Science, Data Science, Machine Learning, Systems Engineering
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