Software Engineer, R&D Platforms
Role details
Job location
Tech stack
Job description
Antares is seeking a Research & Development Software Engineer to build the software systems that enable fast, rigorous experimental engineering across our R&D organization. This role supports test campaigns, prototype development, lab systems, engineering analysis, and verification and validation activities by creating the tools, automation frameworks, data workflows, and hardware/software interfaces that allow engineers to collect high-quality data and make better technical decisions.
The ideal candidate is a strong software engineer who is comfortable near hardware: someone who can write production-quality Python and C++, debug DAQ or networking issues in a lab, structure experimental data, build tools that other engineers actually use, and bring software engineering discipline to a fast-moving R&D environment. We are looking for someone who can operate across the stack, from quick analysis scripts to durable internal tools and test infrastructure, while helping establish the practices and alignment needed for R&D software and V&V workflows to scale.
Roles & Responsibilities:
- Build software-hardware interface tools that support R&D testing, experimental campaigns, prototype development, and engineering analysis.
- Develop test automation frameworks for lab equipment, instrumentation, DAQ systems, sensors, controllers, power supplies, and prototype hardware.
- Create software interfaces to collect, process, store, visualize, and report engineering test data.
- Build internal tools for experiment setup, test execution, data review, anomaly detection, and post-processing.
- Develop Python-based workflows for data acquisition, analysis, visualization, and automated reporting.
- Collaborate with mechanical, electrical, nuclear, controls, manufacturing, and test teams to understand experimental needs and build tools that fit real workflows and develop best practices.
- Support verification and validation (V&V) activities by improving test repeatability, data quality, traceability, and reporting.
- Create lightweight but robust software systems and infrastructure that help engineers move quickly without losing configuration control or data integrity.
- Debug software, instrumentation, networking, DAQ, and hardware-in-the-loop issues in lab and test environments.
- Maintain clear documentation for software tools, interfaces, data schemas, test automation frameworks, and operating procedures.
Requirements
- Bachelor's degree in Software Engineering, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Systems Engineering, Physics, EECS, Nuclear Engineering, or a related technical field.
- 4+ years of experience developing software for engineering, test, R&D, lab, data acquisition, hardware integration, automation, simulation, or analysis environments.
- Strong programming ability in Python and C++.
Preferred Skills and Experience:
- Experience building software that interfaces with hardware, instruments, sensors, controllers, databases, APIs, or engineering tools.
- Experience with test automation, data acquisition, data processing, or engineering analysis workflows.
- Familiarity with software engineering fundamentals: version control, code review, testing, debugging, logging, documentation, and maintainable design.
- Ability to work directly with engineers and translate ambiguous R&D needs into useful software tools.
- Strong data analysis skills and ability to reason from experimental results.
- Strong written and verbal communication skills.
- Experience providing technical leadership, mentorship, or lightweight people management while remaining hands-on.
- Experience aligning software, test, data, and engineering workflows across R&D, hardware, analysis, controls, manufacturing, and operations teams.
- Experience with Python scientific and data tooling such as NumPy, pandas, SciPy, matplotlib, Plotly, Dash, Jupyter, or similar.
- Experience interfacing software with DAQ systems, lab instruments, sensors, serial communication, CAN, Modbus, TCP/IP, OPC UA, MQTT, SCPI, VISA, or similar protocols.
- Experience with NI hardware, LabVIEW, NI-DAQmx, cDAQ systems, or equivalent instrumentation platforms.
- Experience with HIL, SIL, simulation integration, test automation, or digital engineering workflows.
- Experience in regulated, safety-critical, aerospace, defense, automotive, nuclear, or other high-consequence engineering environments.
- Familiarity with requirements traceability, test evidence, configuration management, and engineering quality systems.
- Ability to operate across the stack, from quick scripts to production-quality internal tools, lab interfaces, data infrastructure, and user-facing engineering workflows.