23 Radix Recovery Jobs Hiring Near You

• Design and develop software architectures for automated optical, electrical, MEMS, and system-level test stations.

• Translate engineering test requirements into modular, maintainable, and reusable automation frameworks.

• Integrate laboratory instruments, motion systems, control electronics, DUT interfaces, and supporting hardware into unified test environments.

• Build systems that can evolve from early engineering benches into repeatable validation, qualification, and manufacturing test stations.

• Define station configuration, initialization, calibration, sequencing, error handling, and recovery strategies.

• Develop and maintain instrument drivers and abstraction layers for equipment such as tunable lasers, optical power meters, optical spectrum analyzers, detectors, polarization controllers, motion stages, environmental equipment, FPGA/ASIC boards, and MEMS control electronics.

• Interface with hardware using protocols such as VISA, SCPI, TCP/IP, USB, serial, GPIB, REST APIs, or vendor SDKs.

• Create reusable APIs that allow engineers to interact with complex instrumentation consistently and efficiently.

• Debug communication, synchronization, timing, and hardware/software integration issues across test stations.

• Develop scalable automated test frameworks using Python, C++, LabVIEW/TestStand, or similar technologies.

• Implement test sequencing, parameterization, configuration management, automated calibration, limits checking, and result handling.

• Enable engineers to rapidly create and modify test cases without rebuilding station infrastructure.

• Automate repetitive and time-consuming validation workflows to improve throughput, repeatability, and test coverage.

• Develop tools and interfaces that make complex test stations accessible to optical, hardware, reliability, and validation engineers.

• Build reliable data acquisition pipelines from instrument and DUT readout through structured storage, logging, and downstream analysis.

• Define schemas and metadata structures that preserve device, station, configuration, environmental, and test context.

• Ensure datasets are traceable and reproducible across devices, stations, software revisions, and experiments.

• Support visualization and engineering analysis workflows by providing clean, structured test outputs.

• Implement robust logging, diagnostics, exception handling, and station health monitoring.

• Turn prototype engineering setups into reproducible, documented station platforms that can be deployed across multiple labs.

• Develop station software with scalability, maintainability, version control, and reproducibility in mind.

• Establish Git-based development workflows, code review, automated testing, release management, and documentation practices.

• Support deployment, commissioning, debugging, and maintenance of test stations.

• Partner with manufacturing and operations teams as test platforms move toward pilot and production environments.

• • Work closely with optical characterization engineers to automate established measurement methodologies.

  • Collaborate with photonics, MEMS, hardware, firmware, systems, reliability, and product validation engineers to understand test requirements.

  • Translate experimental procedures into reliable automated workflows while preserving measurement integrity.

  • Instrument test stations to support deeper debug modes, failure analysis, and engineering investigations.

  • Provide feedback on testability and automation requirements as new hardware and products are developed.

• BS or MS in Computer Science, Electrical Engineering, Computer Engineering, Applied Physics, Mechatronics, or a related technical field.

• 5+ years of experience developing software for automated test equipment, laboratory instrumentation, semiconductor test, optical test, hardware validation, or hardware-in-the-loop systems.

• Strong software development skills in Python and/or C++, with Python strongly preferred.

• Demonstrated experience controlling physical instrumentation and hardware through software.

• Experience developing instrument drivers, hardware abstraction layers, automated test sequences, or station-control frameworks.

• Familiarity with interfaces and protocols such as VISA/PyVISA, SCPI, serial, TCP/IP, USB, GPIB, REST APIs, or vendor SDKs.

• Experience building data acquisition, logging, configuration, and structured test-result pipelines.

• Strong software engineering fundamentals including modular architecture, debugging, version control, testing, and documentation.

• Comfortable troubleshooting problems that cross software, instrumentation, electrical hardware, and physical test systems.

• Experience working directly with hardware engineers, scientists, or validation teams in a laboratory environment.

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• Experience automating optical or photonic test equipment, including tunable lasers, optical power meters, OSAs, photodetectors, polarization equipment, or similar instrumentation.

• Experience with silicon photonics, optical transceivers, MEMS, semiconductor devices, or electro-optical systems.

• Familiarity with motion control, FPGA/ASIC test boards, embedded systems, or electromechanical devices.

• Experience with LabVIEW, TestStand, pytest, or other test development frameworks.

• Experience scaling engineering test stations into qualification, pilot-line, or production environments.

• Familiarity with Docker, CI/CD, automated software deployment, or infrastructure for managing multiple test stations.

• Experience designing systems for long-duration reliability testing or high-volume parametric data collection.

• Understanding of basic optical measurements and terminology sufficient to work effectively with photonics engineers.

• Experience using AI-assisted development tools to accelerate software development, debugging, documentation, and engineering workflows.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.