Associate Engineer in the Transmission Planning Modeling team within National Grid’s Graduate Development Program, responsible for developing and maintaining power system models to evaluate grid reliability and plan future transmission investments across New England.
Compensation
Competitive salary ranging from $101,000 to $119,000, plus a comprehensive benefits package
Responsibilities
Develop and maintain transmission planning models used to evaluate system reliability and future grid needs
Update planning cases to reflect transmission projects, generation interconnections, load forecast changes, and system modifications
Perform model validation and quality assurance reviews to ensure planning data accurately represents the transmission system
Collaborate with engineering, operations, and asset management teams to gather, verify, and maintain system information
Support transmission planning studies, including power flow, short-circuit, and system performance analyses
Requirements
Bachelor's or Master's in Electrical Engineering
Nice to have: exposure to power system modeling or analysis software
Support the Distribution Asset Management & Engineering team in North Andover, MA, gaining hands‑on experience in electric distribution engineering and asset management.
Compensation
$24.00 -$35.00 an hour
Responsibilities
Assist with evaluating customer and distributed generation interconnection requests
Analyze system performance and reliability data
Investigate power quality concerns
Support grid modernization initiatives
Develop technical, analytical, and problem‑solving skills
Requirements
Bachelor’s or Master’s degree in Electrical Engineering or Electrical Engineering Technology
Support customers deploying and operating Slinky, debug and resolve issues, develop and maintain software, and collaborate with engineering teams.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 140,000 USD – 224,250 USD for Level 3; and 168,000 USD – 270,250 USD for Level 4.
Responsibilities
Support customers deploying and operating Slinky
Debug and resolve Slinky issues related to deployment, reliability, and performance
Develop, maintain, and optimize Slinky software, Kubernetes integrations, and tooling
Write clean, maintainable, and well-documented code
Build automated tests and troubleshooting tools
Requirements
Bachelor’s degree in Computer Science, Engineering or related field
Lead RF Spectrum Engineer responsible for spectrum sharing, testing, and evaluation across government and commercial systems.
Compensation
Salary compensation range and midpoint:
$156,400 - $195,500 - $234,600 Annual
Responsibilities
Coordinate and lead spectrum sharing test, design, and deployment activities of technical teams from federal agencies, commercial industry, and academia.
Define and execute technical analysis methodologies to determine compatibility of spectrum-dependent systems across commercial and government use cases.
Prepare high quality technical reports, trade studies, engineering recommendations, and sponsor briefings based on analytical findings.
Identify and evaluate emerging technologies that could be utilized to address spectrum coexistence problems.
Provide strategic oversight and manage concurrent components of a broader spectrum-based work program, synchronizing work products across different tasks and organizations.
Requirements
Bachelor’s degree in Electrical Engineering or related field
Master’s degree in Electrical Engineering or related field
PhD in Electrical Engineering or related field
Nice to have: Master’s or PhD in electrical engineering, applied mathematics, physics, systems engineering, or related discipline
Nice to have: 8+ years of professional experience in RF engineering, spectrum engineering, electromagnetic compatibility, or related analytical engineering work
Lead and provide engineering technical direction for complex systems supporting U.S. Navy munition and energetic programs, applying systems engineering principles across all phases of the DoD acquisition process.
Compensation
The projected compensation range for this position is $86,800.00 to $198,000.00 (annualized USD).
Responsibilities
Lead or provide engineering technical direction for problem definition, analysis, development, and implementation of complex systems
Participate in Integrated Product Teams to innovate solutions and develop comprehensive SE plans
Lead system-of-systems integration, including mission and capability planning, reliability and maintainability analysis, human factors considerations
Oversee Integration & Test activities by creating test plans and reports, conducting requirements verification, analysis, and traceability
Produce clear, concise technical documentation tailored to both technical and non-technical stakeholders
Requirements
Bachelor’s degree in Engineering, Physics, or Mathematics
Nice to have: 5+ years of experience with U.S. Navy or armed services directed energy systems research and development programs
Nice to have: experience with DoD technical and engineering requirements in support of NAVSEA programs
Nice to have: experience with combat system integration with command and control, weapon control, networks, display systems, and communications systems
Responsible for testing, analyzing, and troubleshooting electron and ion optics systems to ensure product quality aligns with company and customer requirements in a clean environment.
Responsibilities
Test, analyze, and troubleshoot internal products, test fixtures, and applicable systems to meet company and customer requirements.
Perform analysis, diagnostics, and preliminary evaluations of products.
Analyze customer requirements and develop appropriate testing methods and acceptance criteria.
Repair and maintain test fixtures, lab equipment, and vacuum stations as needed.
Troubleshoot test fixtures, products, and procedures.
Requirements
Bachelor’s degree in engineering, Physics, or a related technical field
Define and drive the AI performance benchmarking and workload characterization strategy across CPU, GPU, APU, NPU, and heterogeneous platforms.
Benchmark AI inference workloads using PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, and related frameworks and runtimes.
Analyze key performance metrics, including latency, throughput, time to first token, tokens per second, memory utilization, power consumption, and performance per watt.
Profile workloads and identify bottlenecks across AI frameworks, runtimes, libraries, drivers, operating systems, firmware, memory subsystems, and hardware.
Lead complex root-cause analysis and recommend optimizations related to quantization, graph execution, kernels, memory usage, workload scheduling, and heterogeneous compute utilization.
Requirements
Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
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