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Synergy ECP · 2 months ago

System Engineer - Machine Learning

Columbia, MD

Full-time

Onsite

Senior Level, Lead/Staff

$180K/yr - $250K/yr

14+ years exp

Synergy ECP is a leading provider of cybersecurity, software and systems engineering, and IT services to the U.S. intelligence and defense communities. The role of System Engineer - Machine Learning focuses on testing the integration of GOTS/COTS Machine Learning models into current product lines, requiring quantitative and qualitative testing along with optimizing system performance.

Cyber SecurityProcurementProject Management

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Testing the integration of GOTS/COTS Machine Learning models into FETS current product line

Characterization of large data sets through some level of automation

Qualification

Machine Learning TestingPythonKubernetesLinuxScripting LanguagesWiresharkData CharacterizationInterpersonal SkillsCommunication SkillsWriting Skills

Required

Fourteen (14) years of experience as a SE in programs and contracts of similar scope, type, and complexity is required

Bachelor's degree in System Engineering, Computer Science, Information Systems, Engineering Science, Engineering Management or related discipline from an accredited college or university is required

Five (5) years of additional SE experience may be substituted for a Bachelor's degree

Strong interpersonal, communications and writing skills

Basic Linux skills required

Although the position is listed as a Systems Engineer Level 2, a well-qualified Systems Engineer Level 1 would be accepted with a strong enough background- B.S. and 7 years of experience, 5 years' experience can be substituted for a degree

CLEARANCE REQUIRED: TS/SCI w/ Polygraph

Other Requirements: U.S. Citizenship

Preferred

Experience Testing Machine Learning Models

Experience with Yolo

Experience with python

Experience with Wireshark or other protocol analyzer

Knowledge of and experience with scripting languages to process automation

Experience installing, monitoring, and optimizing Kubernetes clusters

Familiarity / completion of Advanced Communications Signals Analysis Course (452), Intermediate Communications Signals Analysis Course (452)

Working knowledge of SONET/SDH/OTN, ETHERNET, PCM, VSAT, OSI Model and Computer to Computer (C2C) structure, and/or technologies/protocols such as: MPLS, VLAN, Pseudowire, TDMoIP, ATM, Frame Relay, Cisco, Nortel, TCP, UDP, VCAT, VOIP, VoFR and Voice/Video encoding