以上为北京时间。链接检查不代表仍在招聘，申请前请以招聘官网为准。
按这个岗位的城市和方向提醒，确认后才开启，可选择每日或每周。
高级软件工程师，负责分布式光纤传感边缘平台的设计与开发，构建安全可靠的API和SDK。与数据科学家及ML工程师协作，将原型转化为生产级实时应用。
As a Senior Software Engineer, you become part of a global team developing distributed fiber optic sensing solutions that help optimize critical infrastructure, protect people, and safeguard the environment. Using fiber optic cables as continuous sensors, we combine advanced photonics, measurement technology, and modern software to deliver reliable real-time insights along pipelines, power cables, railways, and other assets. In this role, you contribute to solutions deployed worldwide, working in a collaborative, cross-disciplinary engineering environment that values technical rigor, long-term quality, and practical innovation.
Responsibilities: You will take a key role in shaping and designing our edge platform for developing, testing, deploying, and operating real-time applications. You design and implement secure, reliable, and maintainable platform components, APIs, and SDKs that provide the foundation for robust applications in constrained environments. You work closely with Data Scientists, ML Engineers, and Project Engineers and enable application teams to turn prototypes into production-ready solutions. You contribute to technical direction, engineering best practices, and the long-term evolution of the platform. Company: At AP Sensing, we're building on a success story that began in the garage of Bill Hewlett and Dave Packard. As an independent HP spin-off, we combine over 40 years of technological expertise with a passion for innovation.
You hold a technical degree, ideally in computer science or a comparable field;
You have at least 5 years of professional experience in software engineering, including substantial work on data-intensive real-time systems;
You have excellent programming skills in at least one statically typed language such as Rust (preferred), C++, Go, or similar, and you write high-quality, maintainable code;
You have experience with observability, deployment, monitoring, and operating production systems in distributed or edge-based environments;
You have strong Python skills and practical experience using Python in ML-related tasks, such as data pipelines, model integration, model deployment, or monitoring;
You are comfortable working at the interface between software engineering and applied science and understand the challenges of turning research code into robust production systems;
You quickly understand complex technical and domain-specific problems and break them down into clear, pragmatic solutions;
Ideally, you have experience implementing and operating distributed streaming platforms, IoT systems, or edge-based applications;
Ideally, you have experience with containerized deployments and Kubernetes in test and production environments
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