At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come.
Design, develop, document, integrate, test, and debug software solutions for end-user customers.
Support the architecture, development, and lifecycle management of embedded and real-time systems.
Collaborate with multidisciplinary teams—including Systems Engineering, Digital Engineering, Hardware, and Integration & Test—within an Agile development environment.
Analyze system capabilities to troubleshoot and resolve issues related to program intent, output requirements, data acquisition, programming methods, and control strategies.
Work in a fast-paced lab environment with rapid development cycles.
Conception, développement et maintenance d’applications logicielles pour l’UIT, incluant services cloud, conteneurisation, IA et optimisation de performance.
Compensation
Salaire annuel à partir de $ 71,335 + indemnité de poste $ 59,707
Responsibilities
Conçoit, développe et fournit des applications complètes de bout en bout pour des clients web et/ou bureautiques
Tient à jour, dépanne et optimise les applications existantes
Modernise les bases de code existantes
Crée, déploie et exploite des services natifs de l’informatique en nuage
Applique l’IA tout au long du cycle de vie de l’ingénierie
Requirements
Diplôme universitaire supérieur en informatique, gestion de systèmes informatiques, ingénierie ou sciences ou dans un domaine connexe
Nice to have: Migration de code scientifique (Fortran, ancien C/C++)
Nice to have: Expérience de la création ou de l’exploitation de services sur un grand fournisseur de services en nuage (Azure, AWS)
Nice to have: Expérience de la migration de code scientifique ou d’ingénierie
Nice to have: Expérience de la création de logiciels pour les applications d’ingénierie des radiocommunications
Lead technical design, development, and deployment of autonomous and semi-autonomous robotics systems for construction and industrial equipment.
Compensation
$162,540.00 - $264,120.00
Responsibilities
Define, develop, and bring to production technologies enabling autonomous and semi-autonomous machines
Translate complex customer and machine problems into well-defined technical problems
Evaluate classical robotics and modern learning-based approaches
Rapidly prototype solutions and lead them through integration, validation, and production deployment
Provide technical leadership across robotics systems including perception, sensor fusion, localization and mapping, planning, controls, machine integration, simulation, and intelligent autonomous behaviors
Requirements
Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field
Lead product strategy and roadmap for AI infrastructure stack, defining compiler, runtime, and framework integration features.
Responsibilities
Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
Define requirements for the software and AI model compilation toolchain.
Lead product partnerships and technical integrations with major machine learning frameworks and runtimes.
Define performance optimization roadmap for low-level operator libraries.
Requirements
Master of Science (M.Sc.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Nice to have: MBA
Nice to have: open-source AI infrastructure contributions
Lead product management for AI infrastructure stack, defining roadmap for compiler, runtime, and framework integration.
Responsibilities
Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
Define requirements for the software and AI model compilation toolchain.
Lead product partnerships and technical integrations with major machine learning frameworks and runtimes.
Define performance optimization roadmap for low-level operator libraries.
Requirements
Master of Science (M.Sc.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Nice to have: MBA
Nice to have: open-source AI infrastructure contributions
Provides technical leadership for CT image reconstruction software development, leading subsystem architecture, technical direction, and resolution of complex engineering challenges.
Responsibilities
Lead technical direction for CT image reconstruction software and subsystems
Translate clinical, image‑quality, product, and system needs into software requirements and designs
Define and evaluate technical options for image‑quality, performance, reliability, maintainability, scalability, and cost
Lead root‑cause analysis and resolution of complex image‑reconstruction and system‑level issues
Collaborate with global teams to productize algorithms, integrate systems, and resolve customer issues
Requirements
Bachelor’s degree or higher in Computer Science, Biomedical Engineering, Electrical Engineering, Physics, Medical Physics, or related field
Nice to have: GPU high‑performance software development
Nice to have: AI / deep learning model integration
Nice to have: performance optimization on GPU platforms
Nice to have: advanced image‑quality metrics definition
Lead design, development, and implementation of state estimation algorithms for mobile manipulation robots.
Responsibilities
Design, develop, and integrate robust high-throughput low-latency state estimation, pose estimation, mapping, and reconstruction algorithms for real-world robotic systems
Build simulation-based and on-robot evaluation
Build and maintain algorithms and workflows for intrinsics and extrinsics sensor calibration as well as hand-eye calibration
Translate business and operational requirements into well-scoped technical work packages and execution plans
Collaborate cross-functionally with controls, platform, and hardware engineers to ensure system-level success
Requirements
PhD or Master’s degree
Nice to have: 8+ years of professional software engineering experience
Explore state-of-the-art image and video modeling techniques to improve fraud detection capabilities
Build and optimize end-to-end machine learning pipelines for large-scale datasets
Collaborate with KYC, backend engineering, risk operations and strategy teams to deploy scalable AI solutions
Stay current with advances in computer vision, video understanding and generative AI and translate research breakthroughs into effective risk control solutions
Requirements
Master's degree or above in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision or a related field
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