דרושים » תוכנה » Experienced C++ Developer for Deep Learning Optimization

we are looking for a Core Database Developer (Database Internals) to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization at the center of the revolution in artificial intelligence, which is creating a hurricane of change.
We are looking for a talented Software Engineer to design, build, and optimize the core engine of our high-performance database system. This is a deep, systems-level role focused on the internal workings of a database. You will be responsible for creating the fundamental components that store, retrieve, and process data efficiently.
Key Responsibilities
Design & Develop Database Components: Implement and enhance core database features, including the storage engine, query execution engine, and transaction manager.
Optimize Performance: Work on low-level data structures (like B-Trees or LSM-Trees), concurrency control mechanisms (MVCC), and query optimization algorithms to improve speed and efficiency.
Build the Query Engine: Develop the system that parses, plans, and executes user queries against our data structures.
Ensure Reliability: Implement mechanisms for data recovery, consistency, and durability.

We are seeking an Applied Scientist to help build our next-generation customer memory and personalization systems.

As an Applied Scientist, you will design and build ML and LLM-powered solutions for our customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems.

You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences.
You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage.
You will collaborate closely with engineering and product teams to translate research into measurable customer impact.

We are a Software Embedded Development Engineer to design, develop, and optimize mission-critical embedded software for cloud infrastructure. You will join teams focused on networking, machine learning acceleration, and high-performance computing (HPC), impacting millions of our services globally.

Cutting-Edge Technology: Work on custom silicon (e.g., Graviton, ML accelerators) and innovative networking solutions at the intersection of hardware and software.

Growth & Innovation: Benefit from AWSs resources, mentorship programs, and opportunities to publish technical content.

As a Team Lead, you will lead and mentor a backend development team working on a complex, large-scale medical imaging platform. This role combines Agile leadership with hands-on technical contribution, driving high-quality software delivery in a regulated, customer-focused environment.

Your role

You will act as the Agile facilitator and technical leader of a Radiology Informatics backend team within Image Management in Israel. You will guide the team in delivering scalable, high-performance software that supports advanced PACS solutions used by hospitals worldwide.
Serve as Scrum Master, ensuring effective adoption and continuous improvement of Agile (SAFe) practices
Lead team planning and execution toward iteration and program objectives
Contribute up to 50% hands-on software development and drive technical decision‑making.
Drive complex development efforts and resolve technical blockers
Promote clean, scalable, high-quality code and strong engineering standards
Ensure compliance with development processes, quality metrics, security, and regulatory requirements
Encourage system thinking, domain knowledge, and strong customer focus
Provide clear accountability, remove impediments, and act as an escalation point
Drive innovation through technical reviews, best practices, modern engineering approaches, and the adoption of AI development tools to enhance productivity and code quality
Collaborate with global cross-functional teams and stakeholders
Develop team capabilities through mentoring, delegation, and structured execution.

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence - not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating in our scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

Were looking for an IoT Embedded Linux engineer to design, build, and own the software stack that powers our edge devices in the field. Youll craft resilient Linux-based systems (from bootloader to application), ensure secure and reliable connectivity to the cloud, and work closely with hardware, manufacturing, and backend teams to deliver production-ready devices at scale.
A Day In Your Life :
Own the embedded Linux platform: BSP, kernel configuration, device tree, bootloaders (e.g., U-Boot), systemd services, and startup/upgrade flows.
Develop user-space applications using object-oriented principles (C++/Go/Rust/Similar) to implement core device logic and features, leveraging available libraries and frameworks.
Build production images using Yocto or Buildroot, manage layers/recipes, and maintain reproducible builds for multiple hardware variants.
Implement secure OTA updates (e.g., Mender, RAUC, SWUpdate), with A/B partitions, rollback, and signing-targeting zero‑touch fleet upgrades.
Harden devices for security: filesystem permissions, sandboxing (e.g., AppArmor/SELinux), secure boot/TPM, key management, CVE tracking, and update policies.
Deliver robust connectivity: Ethernet/Wi‑Fi/Cellular (LTE), BLE gateway roles, MQTT/HTTPS, VPN/WireGuard; optimize reliability, roaming, and reconnection logic.
Instrument and debug in the field: journald, core dumps, remote shell, metrics/health checks; trace with strace/perf/tcpdump and diagnose with Wireshark.
Collaborate across disciplines: work with HW, manufacturing, QA, backend, and product to define requirements, provisioning flows, and factory test automation.
Raise the bar on quality: CI/CD for cross‑compilation, unit/integration tests, static analysis, reproducible builds, and fleet-safe release practices.

Come join the Agentic AI science team in building the next generation models for intelligent automation.

We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.