{"id":124025,"url":"https://alion.io/job/true-anomaly-software-engineer-i-perception-new-grad","title":"Software Engineer I, Perception (New Grad)","company":{"id":3381,"name":"True Anomaly","domain":"trueanomaly.space","url":"https://alion.io/company/true-anomaly","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":92,"open_postings":175,"ghost_share":0.046,"stale_share":0,"repost_share":0.006,"time_to_fill_p50_days":101,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Denver, United States","Long Beach, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":98000,"max_usd":200000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1037},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"ONNX","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"Perception","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"ResNet","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"TensorRT","optional":false},{"name":"YOLO","optional":false},{"name":"CNN","optional":true},{"name":"Multimodal AI","optional":true},{"name":"OpenCV","optional":true},{"name":"Quantization","optional":true},{"name":"ROS","optional":true},{"name":"Sensor Fusion","optional":true},{"name":"Synthetic Data","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-08-25T22:01:01Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-23T22:02:45Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":58},"description":"Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.\nOUR MISSION\nTrue Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors - enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.\nOUR VALUES\nBe the offset. We create asymmetric advantages with creativity and ingenuity.\nWhat would it take? We challenge assumptions to deliver ambitious results.\nIt’s the people. Our team is our competitive advantage and we are better together.\nBENEFITS & PERKS*\nBest-in-class healthcare: 100% company-paid medical, dental, and vision coverage for you and your dependents, with HSA/HRA options\n Generous time off: Flexible Time Off (FTO) for exempt employees, accrued PTO of up to 25 days for non-exempt employees, plus 12 paid holidays; Parental Leave; Sick Leave\nFuel for your day: Daily catered lunch and unlimited snacks for in-office employees\n And more: 401(k) retirement plan, fitness reimbursement, and Dog Fridays\nEquity participation: Equity is included as part of our total compensation package, giving you an opportunity to share in the company’s success.\n*Do not apply to fixed term and temporary roles\nYOUR MISSION\nYou'll work on hybrid perception systems combining classical computer vision with modern deep learning for autonomous spacecraft: building multi-object tracking pipelines that fuse neural network detections with Kalman filtering, developing coordinate transformation chains from pixels to orbital frames, training models on synthetic space imagery, and deploying algorithms onboard under strict compute/power constraints.\nYour work enables spacecraft to detect objects against star fields, track multiple targets through occlusions, discriminate threats from decoys, and generate angle measurements for navigation - using both classical geometric methods and learned representations where each approach excels. This is entry-level work blending traditional robotics perception with modern ML. You'll implement Extended Kalman Filters, train neural networks in PyTorch, write C++ flight code, and see your algorithms operate in orbit.\nThis is a 3 month temporary employment engagement. There is potential to convert to regular employment based on performance and business need.\nRESPONSIBILITIES\nImplement classical tracking algorithms: Extended Kalman Filters for state estimation, Hungarian algorithm for data association, track management logic (tentative/confirmed/coasted tracks)\nTrain neural networks for detection and classification: YOLO for object detection, ResNet-based classifiers for threat discrimination, learned appearance features for re-identification\nBuild hybrid perception pipelines: neural network detections → classical tracking → coordinate transformations → angle-only measurements for navigation\nDevelop image processing chains: hot pixel filtering, adaptive thresholding, centroiding, connected component analysis, star catalog matching\nDeploy models to edge hardware: quantize neural networks (INT8), integrate with C++ inference engines (ONNX Runtime, TensorRT), optimize for space-qualified processors\nImplement coordinate transformations: pixel → camera frame → body frame → Earth-Centered Inertial (ECI), accounting for lens distortion and attitude uncertainty\nGenerate synthetic training data: render spacecraft in Blender with domain randomization (lighting, attitudes, backgrounds), create labeled datasets for rare scenarios\nValidate end-to-end performance: software-in-the-loop simulation, processor-in-the-loop testing, hardware-in-the-loop with real camera feeds\nQUALIFICATIONS\nCurrently pursuing or recently completed Bachelor's or Master's degree in computer science, electrical engineering, robotics, aerospace engineering, or related technical field\nCoursework in both computer vision and estimation theory (or willingness to learn both)\nProficiency in Python; some exposure to C++ (we'll teach you more)\nFamiliarity with either classical tracking (Kalman filters, data association) OR deep learning (PyTorch, training neural networks)\nUnderstanding of linear algebra, probability, and coordinate transformations\nAbility to read research papers from both robotics (ICRA, IROS) and ML venues (CVPR, NeurIPS) and implement algorithms\nStrong debugging skills: tracking down lost tracks, numerical instability, and model failure modes\nEagerness to learn the intersection of classical perception and modern ML\nU.S. Citizen (required for facility access and government contracts)\nPREFERRED SKILLS AND EXPERIENCE\nExperience with Extended Kalman Filters, multi-object tracking, or state estimation\nFamiliarity with neural network training in PyTorch or TensorFlow: object detection (YOLO, Faster R-CNN), classification, or segmentation\nUnderstanding of coordinate frames: camera intrinsics/extrinsics, quaternions, rotation matrices, ECI/LVLH/RIC frames\nExposure to model optimization for edge deployment: quantization (INT8, FP16), ONNX, TensorRT\nExperience with OpenCV, image processing pipelines, or classical feature extraction\nCoursework in optimal estimation, sensor fusion, or probabilistic robotics (Kalman/particle filters)\nPrior work with synthetic data generation, Blender/Unreal for rendering, or domain randomization\nUnderstanding of data association algorithms: Hungarian algorithm, auction algorithm, JPDA\nFamiliarity with tracking-by-detection pipelines: detection → association → update → track management\nExperience debugging visual systems: false positives, missed detections, track ID switches, covariance tuning\nPrior internship or project deploying algorithms to embedded systems (Jetson, mobile, ROS)\nExposure to multi-modal perception: fusing camera + IMU, camera + lidar, or learned sensor fusion\nCOMPENSATION\nBase Salary: Denver: $75,000\nLong Beach: $80,000 \n\nYour actual level and base salary will be determinedon a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. \nADDITIONAL REQUIREMENTS\nWork Location -Successful candidates will be located near Centennial, CO or Long Beach, CA.\nWork environment -the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.\nPhysical demands -the physical demands of the job, including bending, sitting, lifting and driving.\nThis position will be open until it is successfully filled. To submityour application, please follow the directions below.\n#LI-Onsite \nTo conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.\nTrue Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.\nTo protect candidates and our company from application fraud and impersonation, we use third-party tools to verify applicant identity and detect fraudulent applications. 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