{"id":702294,"url":"https://alion.io/job/xcimer-senior-scientific-software-engineer","title":"Senior Scientific Software Engineer","company":{"id":685639,"name":"Xcimer Energy","domain":"xcimer.energy","url":"https://alion.io/company/xcimer","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":93,"open_postings":15,"ghost_share":0,"stale_share":0.067,"repost_share":0,"time_to_fill_p50_days":87,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Denver, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":168000,"max":198000,"currency":"USD","period":"year","gross":null,"usd_annual":198000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"CUDA","optional":false},{"name":"Cython","optional":false},{"name":"Docker","optional":false},{"name":"Fortran","optional":false},{"name":"HPC","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"MPI","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"PyBind11","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"SLURM","optional":false},{"name":"STL","optional":false},{"name":"C","optional":true}],"status":"live","first_seen_at":"2026-08-29T03:54:57Z","employer_posted_date":"2026-08-29","last_verified_at":"2026-11-07T09:31:06Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":70},"description":"Xcimer Energy leverages decades of research on Inertial Fusion Energy (IFE) combined with groundbreaking new laser architecture. Our mission is to deploy fusion power plants to meet global decarbonization goals as fast as possible. Xcimer has assembled a team of leaders in tough tech, fusion science, and manufacturing with a track record of rapid execution. Supported by leading investors, Xcimer is uniquely positioned to deliver limitless, clean, fusion power to combat climate change. Join us in powering a better world with inertial fusion!\nThis is a full-time, onsite role based at our headquarters in Denver, CO.\nAs a Senior Scientific Software Engineer, you lead the design and development of software systems that support scientific analysis, visualization, machine learning, and internal applications. You will be part of a high-performing software team working closely with simulation and experimental groups to turn data, models, and control systems into reliable, scalable tools that accelerate R&D.\nThis is a senior, hands-on role with ownership over technical direction and system architecture. A physics background is not required, but you should be comfortable operating in data-driven, research-oriented environments and translating evolving requirements into production-quality software. We are looking for our engineers and scientists to apply their technical expertise, problem solving skills, and dedication to quality to positively impact the future of energy!\nResponsibilities\nSoftware Architecture & Design\nArchitect, develop, and maintain Python-based systems for data analysis, visualization, and internal workflows.\nLead technical design from early research prototypes through production deployment.\nPartner with researchers and engineers to translate experimental and modeling requirements into scalable software solutions.\nEstablish best practices for testing, documentation, CI/CD, and deployment in containerized environments.\nData Pipelines & Analysis\nDesign and support data processing pipelines, including large-scale and streaming datasets.\nBuild interactive, multi-user tools for exploratory data analysis and visualization.\nContribute to machine learning systems, including model integration, training pipelines, and support for real-time or adaptive control workflows.\nPerformance & Integration\nIntegrate Python applications with high-performance computing (HPC) or legacy codes (C++/Fortran) and distributed compute systems.\nOptimize performance-critical components using parallel, GPU-accelerated, or distributed computing techniques as appropriate.\nTechnical Leadership\nMentor engineers and provide technical leadership across projects.\nServe as a senior member of the software team, setting direction and raising the bar for technical quality.\nQualification\nEducation: Bachelor's degree in Computer Science, Engineering, Physics, Applied Mathematics, or related field; advanced degree preferred.\n Experience: 7+ years of professional software development experience in technical, data-intensive, or research-driven environments.\nExpert-level Python skills and strong experience with numerical and data libraries (NumPy, SciPy, Pandas, Matplotlib, Scikit-Learn).\nDemonstrated ability to design and own complex software systems under ambiguous or evolving requirements.\nExperience collaborating closely with non-software domain experts and supporting experimental or simulation workflows.\nMust be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.\nDesired\nExperience working with 3D geometry or CAD data (STEP, IGES, STL, BREP) and related libraries (OpenCASCADE, VTK, PyVista).\nFamiliarity with structured scientific data formats (HDF5, NetCDF, VTK, custom binary formats).\nExperience interfacing Python with C/C++ or Fortran (pybind11, Cython, f2py, nanobind).\nStrong background in parallel, GPU, or distributed computing (MPI, CUDA, OpenACC).\nExperience with machine learning systems in production environments.\nBackground supporting real-time systems, feedback loops, or adaptive control applications.\nExperience with containerization and orchestration (Docker, Apptainer, Kubernetes) as well as HPC environments and job schedulers 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