דרושים » תוכנה » Quantitative Researcher

Required Senior Software Engineer - C/C++
Responsibilities:
Design, develop, and maintain production-grade software using C++ and Python.
Build modular, well-architected components following object-oriented design principles.
Optimize code for real-time and low-latency operation.
Collaborate with cross-functional teams to deliver end-to-end solutions.
Write clean, maintainable, and well-tested code.

Required Sr. MacOS Sensor Engineer, Data Security (Hybrid, ISR)
About the Team:
You'll be joining the Data Protection Team in our Data Security Product Group, whose
mission is to build a unified data security system which enables customers to identify and investigate insider threats, identify access to and movement of sensitive data, and ensure regulatory compliance by mitigating data loss risk.
About the Role:
We are a two-component security product. One component is a sensor: a driver installed on client machines that observes system activity and recognizes malicious behavior, then provides on-box prevention capability and remote telemetry to the Falcon Host cloud. The sensor processes thousands of events per second to provide deep visibility into operations on the endpoint, and performs rich correlation and computation to identify malicious events and blocks malicious activity.
The cloud component aggregates sensor telemetry for each customers network, correlates malicious behavior across multiple machines, and presents our customers operations teams with a prioritized summary of the threats detected in their environments.
This is a macOS Developer role in the engineering team that delivers data protection-focused functionality in the sensor (lightweight agent) on macOS. Engineers in the team own the design and development of core features on the platform. Data protection-focused functionality centers around file interfaces, including related Endpoint Security System Extension interfaces. The team operates under the Agile development principles and ships frequently.
What You'll Do:
Design and develop data protection-focused system extensions and associated services for deployment on macOS systems
Own features from design to delivery
Collaborate with multi-functional team in various physical locations
Troubleshoot issues with the product as reported from customers responsively
Other projects as assigned.

We are looking for a Senior Software Engineer to join the development of state-of-the-art automotive imaging radar technology.
Our vision is to bring new and cutting-edge automotive radar sensor solutions, while leveraging our assets and expertise in this field. Introducing best in class Radar sensor that would complement our end-to-end autonomous driving solution platform.
You will be part of a winning team in a fast-paced startup-like environment, working on many different components of the entire system. You will have an opportunity to make an impact on the design and implementation of an innovative technology in its early stages.
What will your job look like:
Design, build and optimize software modules for production grade imaging-radar solution Implement complex algorithms in a multi-core platform with high bandwidth with distributed memory.
Work closely with research team to implement highly complex DSP algorithms
Plan memory arrangement, data transfer, pipeline of computation and multi-core utilization to maximize performance in low-resources compute-limited environment

We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure. This role requires deep system-level architecture understanding, the ability to handle large-scale clusters processing petabytes of data, and mastery of modern C/C++ and Linux environment internals.
Key Responsibilities
Design & Develop Core Components: Build, maintain, and optimize highly scalable, resilient distributed services, storage engines, or data-processing pipelines written in C/C++.
System Architecture & Resilience: Drive architectural discussions and implementations around high availability, data consistency, replication mechanisms, fault tolerance, and multi-node concurrency.
Performance Optimization: Optimize hot execution paths, low-level data structures, memory management, and I/O subsystems to guarantee high throughput and minimal latency.
Complex Debugging & Troubleshooting: Investigate and resolve intricate production issues spanning the application layer, distributed networking protocols, file systems, and operating system kernels.
End-to-End Ownership: Take full technical ownership of critical features-from ambiguous requirements and system design through implementation, rollout, and observability in production environments.
Teams
Storage Platform: Focuses on building a next-generation distributed storage platform handling petabytes of data across large clusters specifically designed to power AI, enterprise, and analytics workloads. Handling everything that touches the hardware and operating system aspects in a software defined storage system
Data Path: Focuses on engineering a highly distributed, latency-critical Hot I/O Data Path and Element Store engine. This role is responsible for the ingestion, state-of-the-art compression, encoding, and retrieval of multi-protocol data (files and objects) under massive concurrency and ultra-low latency requirements.
Database: Focuses deeply on core relational database internals, specifically designing low-level storage engines, B-Tree/LSM-Tree data structures, MVCC concurrency control, and query execution planners.
Kernel: Focuses on the lowest software layers, emphasizing Linux Kernel development and block-level storage/file system engineering.
Protocols: Focuses strictly on engineering high-concurrency data/metadata paths that replicate external AWS S3 object-storage behavior and correctness under heavy retry and failover pressure.
Cloud: Focuses on cloud-native storage deployment, adapting and scaling complex high-availability storage infrastructure across major hyper-scaler cloud environments (AWS, Azure, GCP).
Compute Kafka: Focuses on distributed event-streaming and messaging platforms, specifically building a high-scale, exactly-once broker compatible with the Apache Kafka wire protocol.