{"id":2550248,"url":"https://alion.io/job/saaz-senior-computer-vision-algorithmsoftware-engineer","title":"Senior Computer Vision Algorithm/Software Engineer","company":{"id":4390064,"name":"Saaz","domain":"saaz.com","url":"https://alion.io/company/saaz","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["Camarillo, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":126000,"max_usd":240000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1213},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenCV","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"PyTorch C++","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-08-14T00:00:00Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-10-17T03:15:42Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":64},"description":"SAAZ is seeking an exceptional Senior Computer Vision Algorithm & Software Engineer to architect and implement advanced processing pipelines for next-generation electro-opticaland infrared (EO/IR)imaging systems.\nThis multidisciplinary role bridges theoretical research and high-performance software engineering, requiring hands-on expertisein image processing, computer vision, convolutional neural networks (CNNs), or spiking neural networks (SNNs) rather than traditional application software development alone. Operating with a high degree of autonomy, the successful candidate will hold a graduate degree-preferably a PhD-and possessthe independent drive to conceptualize, design, and deploy sophisticated algorithms from scratch without direct supervision.\nWorking closely with Firmware, FPGA, Systems, and Product Engineering teams, you will drive algorithmic innovation for advanced camera products deployed in aerospace, defense, and commercialimaging, guiding developments from concept through hardware-software integration and production.\nKey Responsibilities:\nAlgorithm Architecture & Conceptualization: Design, prototype, and refine advanced image processing and computer vision algorithms-including traditional image enhancement, noise reduction, and modern deep learning models (CNNs/SNNs)-tailored for EO/IR sensor architectures.\nAutonomous End-to-End Implementation: Independently translate mathematical models and theoretical concepts into high-performance, maintainable software implementations without needing direct step-by-step supervision.\nCross-Functional System Integration: Collaborate closely with Firmware, FPGA, and Systems Engineering teams to optimize, port, and validatealgorithms on real-time target hardware and embedded camera processing platforms.\nEO/IR Pipeline Optimization: Develop and tune edge-detection, feature extraction, non-uniformity correction (NUC), dynamic range expansion, object detectionand tracking algorithms specialized for complex electro-optical and infrared environments.\n\nResearch & Feasibility Trade Studies: Conduct independent trade studies, literature reviews, and rapid prototyping to evaluate novel machine learning and spiking neural network (SNN) approaches for low-power or bandwidth-constrained imaging systems.\nVerification & Testing Pipelines: Build robust simulation environments, ground-truth dataset collection methodologies, and automated testing frameworks to evaluate algorithm accuracy, latency, and performance edge cases.\nTechnical Documentation & Mentorship: Document mathematical formulations, algorithmic trade-offs, and software architectures to support production handover, system qualification, and intellectual property development.\nMinimum / Required Qualifications:\nEducation & Experience: Master’s degree in Electrical Engineering, Computer Science, Applied Mathematics, Optical Engineering, or a closely related field with 5+ years of hands-on algorithmic experience, or a Ph.D. with 2+ years of relevant research/industry experience.\nDomain Expertise: Proven hands-on track recorddeveloping and deploying core image processing, computer vision, or neural network models (CNNs or SNNs). Pure application software development without signal processing or computer vision experience will not be considered.\nEO/IR Pipeline Knowledge: Direct familiarity with physical imaging concepts and sensor data pipelines, such as non-uniformity correction (NUC), bad pixel replacement, dynamic range compression, or thermal/optical noise reduction.\nCore Technical Stack: Proficiencyin C/C++ and Python for rapid prototyping, algorithm implementation, and performance benchmarking.\nMathematical Foundations: Strong foundationin linear algebra, multi-variable calculus, spatial/frequency-domain filtering, and statistical signal processing.\nAutonomous Execution: Demonstratedability to drive projects independently from literature review and mathematical formulation through to functional code without daily supervision.\nPreferred Qualifications:\nAdvanced Degree: Ph.D. focusing on Computer Vision, Spiking Neural Networks (SNNs), Neuromorphic Computing, or Infrared Image Processing.\nHardware-Aware Software Optimization: Experience adapting heavy algorithmic models or neural networks for resource-constrained platforms, such as embedded GPUs (NVIDIA Jetson), FPGAs, or specialized DSP architectures.\nAdvanced Neural Architectures: Hands-on research or deployment experience with Spiking Neural Networks (SNNs), event-based neuromorphic sensors, or ultra-low-latency event processing for edge execution.\nSpecialized EO/IR Algorithms: Background in real-time object detection/tracking, multi-sensor data fusion (EO/IR registration), or high dynamic range (HDR) image reconstruction.\nSimulation & Frameworks: Expertisewith deep learning and vision frameworks (e.g., PyTorch, OpenCV, TensorRT, LibTorch) alongside customized C++ execution pipelines.\nSuccess Metrics:\nAlgorithms execute within defined latency, framerate, and real-time processing constraints.\nCPU, GPU, and embedded memory utilizationremain within target resource budgets.\nAlgorithms achieve specified precision, recall, and detection/tracking accuracy metrics across target EO/IR datasets.\nCode passes performance, memory leak, and static analysis checks without critical warnings or errors.\nCompliance with project coding, testing, and documentation standards.\nUnit, integration, and ground-truth simulation tests successfully completed.\nSeamless pipeline integration and data throughput achieved across cross-functional interfaces (Firmware, FPGA, host APIs).\nAlgorithmic robustness validatedunder adverse real-world conditions (e.g., thermal drift, low contrast, high dynamic range, atmospheric noise).","description_format":"text","description_chars":5747,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotic Software & Control Systems"],"lifecycle":[{"event":"open","at":"2026-10-14T17:47:55Z"}],"visa":[],"liveness":{"score":13,"band":"cold","label":"Long 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