דרושים » תוכנה » Manager, Software Development (Hands-On Technical), ML Network Stack

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 Senior Software Development Engineer who leads through technical depth and sound judgment. Someone who owns team-level architecture, provides system-wide design guidance, and brings perspective on both current and future technology choices. You take on customer problems where the technological strategy is not yet defined, and you drive productive discussions to align teams on the best path forward. You dont just deliver high-quality software yourself - you set the standard that others follow. You actively mentor multiple engineers, drive adoption of engineering best practices, and ensure your team has strong operational foundations. You make the team permanently stronger, not dependent on your presence. When the right solution isnt technical - when its a process change, a culture shift, or a staffing decision - you recognize that and act accordingly.

Key job responsibilities
- Own team architecture of personalized recommendation system operating in our scale.
- Lead the design and delivery of cross-teams projects end-to-end, with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define technical roadmap and experiences based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and drive measurement strategies including analytics events and experiment configurations to track business and technical metrics.
- Create clarity from ambiguity and make sound technical decisions in a problem space where established patterns don't apply.
- Drive adoption of engineering best practices through exemplary personal coding practices.
- Proactively simplify existing systems and resolve endemic, root-cause problems.

We are seeking a highly technical Developer Relations Manager to join our team, with a focus on engaging deep collaborations with the next generation of security companies building solutions for the AI and Agentic era. In this role, you will work directly with security companies, guiding them on how to leverage our software stacks when developing solutions to secure AI and Agentic environments and workloads. The ideal candidate brings a blend of deep technical expertise and commercial go-to-market experience, combined with a passion for developer advocacy and a talent for communicating how our technology can solve complex, real-world challenges.
What You'll Be Doing:
Serve as the trusted technical advisor, problem solver, and champion for the developer ecosystem in the AI and Agentic Security industry with cross-functional partners to drive adoption of our technologies.
Accelerate critical workloads by demonstrating groundbreaking solutions that integrate the core stack into developer products, platforms, and pipelines.
Guide partners and startups through onboarding and integration with our programs, fostering co-innovation and the development of next-generation solutions.
Map, track, and monitor the developer ecosystem to identify growth opportunities, inform technology roadmaps, and shape adoption strategies.
Collaborate multi-functionally with solution architects, engineering, product management, and marketing to drive developer engagement and optimize partner adoption strategies.
Represent and advocate for the partner technical needs and feedback to our internal product and engineering teams, supplying actionable insights from field deployments to influence product roadmaps.

Required Engineering Manager, Cloud Storage
About the job
Like our own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
File Solutions is the file system in the cloud from. Filestore provides a fully managed NFS service for Enterprise Cloud users which need file storage to replace their on-premise hardware when they move to the Cloud. This is an addressable market, with an opportunity to attract enterprises shifting to the cloud.
Responsibilities
Impact Control Plane definitions, design and methodologies for a new Software (SW) infrastructure.
Collaborate with various stake-holders, technical leaders, engineering managers and SWEs in order to fulfill team's mission and plan.
Grow and mentor the team, help others achieve career goals, identify roadblocks, prioritize efforts and reduce ambiguity.
Own plan and execution, working on multiple user facing features and architecture tasks.
Work with peers from other aspects of the product development life-cycle, including all File store engineering teams, product management, program management, SRE, UX/UI.

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 at 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.

A leading and innovative company in the field of cyber threat intelligence is looking for an experienced Engineering Group Leader to join the executive team and lead the technological development efforts. The role includes managing and building full-stack engineering teams, overseeing architecture and product development, recruiting engineers, defining development processes and technology standards, and driving a tech strategy that supports the companys growth and business goals.

What Youll Be Doing

Lead and manage multiple engineering teams, including team leads and senior engineers.
Mentor, coach, and develop engineers and engineering leaders, fostering a strong growth-oriented culture.
Take end-to-end ownership of delivery, quality, and reliability for your groups products and services.
Translate high-level engineering and product strategy into clear execution plans and milestones.
Collaborate closely with Product Management to plan roadmaps, prioritize work, and align on scope and delivery.
Participate in architectural discussions and contribute to technical and design decisions.
Implement, maintain, and continuously improve development processes (Agile/Scrum).
Play an active role in hiring, onboarding, and retaining top engineering talent.
Work closely with other engineering managers and senior leadership to ensure alignment across teams and domains.

The MLIL DataPlane team is looking for a Senior Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need a senior IC who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures (decoder-only, mixture-of-experts) end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.
- Mentor engineers, drive design reviews, and raise the engineering bar across the team.

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.

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.

We are looking for an experienced SRE Team Lead to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will lead a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 3-4 years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.



What will you do?

Leadership & Team Management

Lead, mentor, and grow a team of SREs, providing technical direction, career development guidance, and day-to-day management.

Own the team roadmap for reliability, observability, and automation initiatives - prioritizing work, removing blockers, and driving delivery.

Conduct regular 1:1s, performance reviews, and hiring processes to build and sustain a high-performing team.

Foster a culture of operational excellence, blameless post-mortems, and continuous improvement.

Act as an escalation point for complex incidents and reliability issues, leading post-incident reviews and ensuring follow-through on action items.


Automation & Infrastructure

Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.

Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.

Drive the adoption of infrastructure-as-code practices across the organization.

Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.


Monitoring & Observability

Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.

Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.

Define and track SLIs, SLOs, and error budgets across key services.

Partner with development teams to embed observability earlier in the software development lifecycle.


Database & Platform Support

Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.

Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.