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Software Systems Engineer and Scientist— AI/ML Micro-Sensor Systems

Levels: Entry-Level / Associate, Mid-Level, Senior / Principal

Employment Type: Full-time

Work Environment: Collaborative, hands-on, AI-centric research, design, integration, and test environment

Citizenship Requirement: U.S. CITIZENSHIP REQUIRED

Position Summary

We are seeking innovative Software Systems Engineers and Scientists, from entry-level through senior/principal levels, to help conceive, develop, integrate, and validate next-generation AI/ML-enabled multidimensional micro-sensor systems.

Successful candidates will work in a creative, fast-moving technical environment where advanced artificial-intelligence tools, model-based engineering, automated test, simulation, and hands-on laboratory experimentation are integral to the design process. The role spans early concept development through deployed-system verification, including system architecture, requirements definition, software and algorithm development, sensor-data processing, hardware/software integration, and performance characterization using advanced instrumentation.

The ideal candidate can move between high-level system thinking and detailed technical execution: translating mission and customer needs into measurable system specifications; developing robust software architectures, algorithms, and analytics; designing experiments; collecting and interpreting multidimensional sensor data; and using results to improve system performance.

Applications may include compact sensing platforms, embedded and edge-AI systems, distributed sensor networks, RF and electromagnetic sensing, autonomous or uncrewed platforms, industrial monitoring, aerospace and defense systems, and other emerging intelligent-sensor applications.

Core Responsibilities

·       Envision and define innovative system solutions for AI/ML-enabled multidimensional micro-sensor products and platforms.

·       Translate customer, mission, operational, and technical needs into clear, traceable system requirements, interfaces, architectures, specifications, and verification plans.

·       Develop software, algorithms, models, and tools supporting sensor control, data acquisition, calibration, processing, fusion, visualization, analytics, and system-health monitoring.

·       Design and implement AI/ML approaches for classification, detection, anomaly identification, prediction, sensor fusion, adaptive sensing, edge inference, and automated decision support.

·       Participate in the complete engineering lifecycle: concept development, architecture, requirements, detailed design, implementation, integration, test, verification, validation, documentation, and transition to production or field deployment.

·       Develop and execute laboratory and field-test plans using advanced instrumentation, automated test equipment, data-acquisition systems, environmental-test resources, and custom test fixtures.

·       Analyze complex multidimensional data sets to quantify sensor, algorithm, and system performance; identify root causes; and recommend corrective actions or design improvements.

·       Integrate software with embedded processors, FPGAs, microcontrollers, sensor interfaces, communications links, cloud or edge-computing resources, and test equipment, as applicable.

·       Develop reusable internal tools, software frameworks, test automation, data pipelines, simulation environments, and engineering workflows that improve development speed, traceability, technical quality, and repeatability.

·       Collaborate with scientists, electrical engineers, RF/microwave engineers, firmware and FPGA developers, mechanical engineers, test engineers, program managers, customers, and external partners.

·       Prepare technical documentation, including architecture descriptions, interface-control documents, requirements specifications, test procedures, test reports, design-review materials, and customer deliverables.

·       Maintain awareness of emerging AI/ML methods, sensor technologies, software-development practices, instrumentation capabilities, and relevant commercial and government technology trends.

Entry-Level / Associate Expectations

Entry-level engineers and scientists will work under the guidance of experienced technical staff while building broad experience in AI-enabled sensing systems, embedded and systems software, engineering analysis, and laboratory test.

Typical responsibilities include:

·       Assist with software development, data analysis, algorithm prototyping, test automation, and sensor-data collection.

·       Support requirements decomposition, design documentation, interface definition, and system-verification activities.

·       Develop scripts, utilities, dashboards, and analysis tools for laboratory and field-test data.

·       Assist with integration and troubleshooting of sensor hardware, embedded platforms, data-acquisition equipment, and software systems.

·       Operate laboratory instrumentation and automated test equipment under approved procedures.

·       Participate in design reviews, technical brainstorming, demonstrations, and customer-facing technical activities.

·       Learn and apply sound practices for software configuration management, documentation, cybersecurity, quality assurance, and test discipline.

Senior / Principal Expectations

Senior and principal engineers and scientists will provide technical leadership across the system lifecycle and help establish the architecture, technical strategy, and execution approach for complex sensor-system programs.

·       Lead system concept development, architecture definition, requirements allocation, and technical trade studies for AI/ML-enabled sensor systems.

·       Define scalable software, data, and test architectures spanning embedded, edge, distributed, and cloud-connected elements, where appropriate.

·       Lead the design and implementation of advanced AI/ML algorithms, sensor-fusion architectures, data-processing pipelines, and automated verification capabilities.

·       Establish quantitative performance metrics, test strategies, acceptance criteria, and verification methods for multidimensional sensing systems.

·       Lead complex integration, troubleshooting, root-cause analysis, and corrective-action efforts involving software, algorithms, sensors, electronics, embedded platforms, and instrumentation.

·       Serve as a technical lead or principal investigator on internal R&D, customer-funded development, aerospace, defense, industrial, or commercial programs.

·       Mentor junior engineers and scientists, conduct technical reviews, and strengthen organizational standards for engineering rigor, software quality, automation, security, and innovation.

•  Contribute to proposals, technical roadmaps, customer briefings, product definitions, intellectual-property development, and technology-transition strategies.

Entry-Level / Associate

·       Bachelor’s degree in computer science, software engineering, electrical engineering, computer engineering, physics, applied mathematics, data science, systems engineering, or a related technical discipline.

·       Demonstrated interest or coursework in software development, embedded systems, AI/ML, data science, signal processing, sensors, robotics, controls, or systems engineering.

·       Familiarity with one or more programming languages such as Python, C, C++, Rust, MATLAB, Julia, or similar languages.

·       Ability to analyze technical problems, learn rapidly, communicate clearly, and work effectively in a multidisciplinary engineering team.

·       Interest in hands-on development, laboratory work, debugging, measurement, testing, and iterative prototyping.

Senior / Principal

·       Bachelor’s degree plus 8+ years of relevant experience, master’s degree plus 5+ years, or Ph.D. plus 2+ years; equivalent combinations of education, research, and professional experience will be considered.

·       Demonstrated experience leading or making major technical contributions to complex software, AI/ML, sensor, embedded, autonomous, cyber-physical, signal-processing, or systems-engineering programs.

·       Strong experience with systems engineering, requirements development, architecture definition, interface management, verification planning, and technical trade studies.

·       Proven ability to take an ambiguous technical problem from concept through architecture, detailed design, integration, test, and customer demonstration or deployment.

Strong technical writing and communication skills, including the ability to produce specifications, design documentation, test reports, and customer-facing technical materials.

Desired Technical Qualifications

Candidates are not expected to possess every qualification. We welcome applicants with depth in several of the following areas:

·       AI/ML model development, training, optimization, validation, deployment, monitoring, or edge inference.

·       Machine-learning frameworks such as PyTorch, TensorFlow, JAX, scikit-learn, ONNX, or equivalent tools.

·       Sensor-data processing, multisensor fusion, time-series analysis, classification, detection, tracking, anomaly detection, or predictive analytics.

·       Embedded software, real-time operating systems, Linux, device drivers, hardware-abstraction layers, microcontrollers, SoCs, GPUs, NPUs, or FPGA-adjacent software development.

·       Python, C/C++, MATLAB, data-analysis workflows, software-test frameworks, version control, continuous integration, containerization, and reproducible development environments.

·       Systems modeling and simulation, digital engineering, model-based systems engineering, SysML/UML, MATLAB/Simulink, or equivalent tools.

·       Laboratory instrumentation and automation, including oscilloscopes, spectrum analyzers, vector signal analyzers/generators, network analyzers, logic analyzers, power analyzers, DAQ systems, environmental-test equipment, and custom automated-test systems.