דרושים » הנדסה » Software Engineer, Systems

we are looking for a Software Engineer to build and scale product experiences used by billions of people across our company, Instagram, WhatsApp, and Messenger. In this role, you will own the full software development lifecycle for consumer-facing or platform-level features, partnering closely with product management, design, and data science to define requirements, architect solutions, and ship high-quality, reliable systems at global scale.
Software Engineer, Product Engineering Responsibilities
Design, build, and maintain scalable full-stack product features across web and mobile platforms, from API design through front-end implementation
Own the technical design of product systems, evaluating architectural trade-offs to meet well-defined business requirements and drive engineering value
Instrument features with telemetry, dashboards, and alerting to establish observability before and during rollout, and use data to drive product and performance decisions
Run and review experiments using A/B testing frameworks to validate product hypotheses and make data-informed decisions that balance short-term goals with long-term quality
Manage staged feature rollouts using feature flagging systems, proactively monitoring for regressions and driving mitigation during incidents
Identify and resolve complex bugs across the stack, including non-reproducible and multithreaded issues, and implement defensive programming practices to prevent recurrence
Collaborate with product managers, designers, and data scientists to translate product requirements into technical specifications and executable engineering plans
Drive improvements to engineering efficiency by identifying bottlenecks in team workflows, building tooling and automation, and completing migrations that eliminate legacy code
Mentor other engineers on the team by sharing technical feedback, identifying growth areas, and contributing to code review standards and best practices
Proactively incorporate privacy, security, and integrity principles into early engineering stages and partner with cross-functional teams to ensure appropriate safeguards are in place.

Meta is seeking a Machine Learning Engineer to design, build, and deploy machine learning systems across a broad range of product areas including ranking, recommendations, natural language understanding, computer vision, and integrity. In this role, you will own the full ML development lifecycle - from data pipeline construction and feature engineering through model training, evaluation, and production deployment - contributing directly to systems that serve billions of users at global scale.
Machine Learning Engineer Responsibilities
Design and implement end-to-end machine learning pipelines spanning data ingestion, feature engineering, model training, offline evaluation, and production serving
Develop and optimize models for large-scale applications such as ranking, recommendations, classification, and natural language understanding
Instrument model performance with robust monitoring, alerting, and dashboards to detect regressions and maintain production reliability
Drive A/B experiment design and analysis to validate model improvements, articulate trade-offs, and make data-informed launch decisions
Architect scalable ML infrastructure and reusable components that accelerate development velocity across the team
Identify and resolve complex model quality issues through systematic debugging, root cause analysis, and defensive engineering practices
Collaborate with product managers, data scientists, and software engineers to translate product requirements into ML problem formulations and technical roadmaps
Define and evolve ML platform standards, coding best practices, and testing frameworks to improve engineering quality across the organization
Mentor other engineers on ML methodology, system design, and engineering craft, and contribute to recruiting by conducting technical interviews.

Meta is reimagining shopping on our company, Instagram, and Muse. The vision is to make every piece of media shoppable. Behind that vision is our Product Recognition and Intelligence stack. It is the tech that looks at any photo, video, and text, and knows exactly which products are in it and how they relate to other products. We are building it to work at Meta's scale. Over 3 billion distinct users every day. Billions of items power a multibillion-dollar ad business.
We are hiring a senior staff Machine Learning Engineer to lead this journey. You will tackle the hardest ML systems challenges in training, serving, and evaluation. You will set the architecture and standards that raise the bar across organizations. You will ship state-of-the-art models to production where they touch billions.
If you want to have an impact at a global scale and love building tech that actually ships, come build with us.
Software Engineer - Machine Learning (Technical Leadership) Responsibilities
Identify and solve the most complex machine learning systems problems across the organization, including model training efficiency, large-scale inference optimisation, and cross-system ML pipeline reliability
Define and own the technical architecture for critical ML infrastructure components, ensuring designs are extensible, maintainable, and capable of supporting the next generation of model development at Meta's scale
Establish engineering standards and invariants for ML systems that prevent entire categories of reliability, correctness, and performance issues across multiple teams
Drive cross-organizational technical strategy by assessing emerging ML technologies, evaluating trade-offs between competing approaches, and influencing roadmap decisions with leadership and cross-functional partners
Lead the design and delivery of org-wide ML platform initiatives, coordinating across engineering teams, research, product, and data science to align on priorities and drive execution through ambiguity
Develop new metrics and data-driven frameworks for evaluating ML system health, model quality, and infrastructure efficiency, and connecting them to organization-level goals
Mentor and coach engineers across the organization on ML system design, debugging complex models and infrastructure failures, and developing scalable solutions to recurring technical challenges
Collaborate with privacy, security, and compliance teams to design ML systems that uphold user safety, meet regulatory requirements, and set the standard for responsible AI practices within the business domain
Identify and eliminate engineering bottlenecks through improved tooling, automation, and process improvements that make ML development faster and more reliable across the organization
Contribute to recruiting efforts by building relationships with candidates who bring critical ML systems expertise, and serve as a technical reference point for evaluating engineering talent at the most senior levels.

run:ai, is looking for a senior software engineer to build the tools that help engineers develop, validate, and contribute software with confidence. as we expand our open-source ecosystem and adopt agentic development, you'll shape how contributions are tested and integrated, improve feedback for developers, and help protect our codebase and internal assets. you'll work across Developer tooling, compatibility validation, scale testing, and ai-assisted contribution workflows, building infrastructure that supports both our engineering teams and the wider open-source community.
what you'll be doing:
build Developer tools and ci workflows that simplify development, testing, and contribution for internal engineers and open-source contributors.
develop compatibility validation infrastructure that verifies run:ai across supported software versions and environments.
build scale-testing and performance-regression infrastructure that produces repeatable results and actionable diagnostics.
develop workflows for agentic prs, including automated evaluation, testing, and controls that support effective human review.
partner with engineering, DevOps, and security teams to enable external contributions while protecting credentials, internal systems, and code integrity.
own projects from technical design through rollout, measuring their impact on Developer productivity and software reliability.

we have been defining computer graphics, pc gaming, and accelerated computing for more than 25 years. with an outstanding legacy of innovation, driven by phenomenal technology and extraordinary people, we are looking for a distinguished engineer to help shape the future of ai infrastructure. as part of our advanced development and research efforts, you will drive technical vision and innovation across the ai software stack, spanning gpu computing, rdma, nvlink, Storage, and large-scale distributed systems. you will research next-generation system designs, influence product and platform direction, and help define how massive-scale ai environments are built, optimized, and operated through hardware-software co-design.
what you'll be doing:
research, define, and drive co-design solutions across ai software stacks involving gpu computing, rdma networking, nvlink interconnects, Storage, and large-scale distributed infrastructure
lead deep technical investigations and proof-of-concept development in areas related to distributed ai, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design
work closely with multiple teams across the company to advance next-generation ai infrastructure technologies and influence cross-stack co-design decisions
analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and Storage layers to improve performance, scalability, and efficiency
guide the design of environments that support massive-scale ai training and inference workloads in production
 we want to hear from you!
we are committed to fostering a diverse work environment and proud to be an equal opportunity employer. as we highly value diversity in our current and future employees, we do not discriminate, including in our hiring and promotion practices, on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

As a Senior Principal DevOps Engineer, you will serve as a visionary technical leader within the Cortex Cloud DevOps group. You will define the technical strategy and architecture that ensures our massive-scale production services remain highly reliable, exceptionally secure, and performant. You will pioneer the integration of AI-driven capabilities into our daily operations, establishing elite engineering standards and fundamentally transforming the workflows of hundreds of developers through autonomous agents and intelligent procedures.
Your Career
Architectural Vision & Scalability: Design and scale massive, resilient distributed systems and global Kubernetes infrastructure, implementing robust observability and monitoring frameworks.
AI-Driven Transformation: Revolutionize the SDLC by integrating Generative AI, autonomous agents, and LLM-powered workflows into CI/CD and self-healing systems to accelerate developer velocity.
Technical Leadership & IaC: Define architectural standards, lead GitOps/IaC (FluxCD/Terraform) strategies, and mentor Senior/Staff engineers across the R&D organization.
Developer Experience & Efficiency: Build and champion AI-powered platforms that automate troubleshooting and eliminate friction. Partner directly with Engineering Directors, Principal Architects, and Product Management to align infrastructure initiatives with business goals, optimizing for scale, high availability, and multi-million-dollar cost-efficiencies.
Security & Compliance: Embed "Security by Design" principles into the platform architecture to ensure platform integrity without sacrificing delivery speed.

Were looking for an experienced Team Leader who wants to make a foundational impact on the engine that powers cloud security platform.
Our Stack: Python, AWS, Kafka, Redis, SQS, Postgres, Kubernetes. Our scanning surface extends across Azure, GCP, OCI and Alibaba Cloud and others.
What Youll Do:
Lead, mentor and develop a team of senior software engineers through one-on-ones, feedback and technical guidance
Own and drive the delivery of high-impact projects end to end, from design through deployment and production monitoring
Design and review architecture for large-scale distributed systems, with a focus on scalability, resilience and efficiency
Drive the platforms scalability and cost efficiency as scan volumes grow
Collaborate cross-functionally with Product, SRE and other R&D teams to define priorities, interfaces and success metrics
Ensure the reliability, scalability and observability of core services, introducing SLOs and best practices for operations
Uphold the teams engineering standards for code quality, safe rollout of changes and long-term maintainability
Write and review clean, maintainable and tested code

We are looking for a Senior Software Engineer to solve complex technical problems and build dependable backend and platform systems that enable our product to scale. You will own work from design through production, balance near-term delivery with long-term maintainability, and help teammates grow.

What youll do
Design, implement, and operate scalable backend services, APIs, and platform capabilities.
Build robust systems and services in Go and Python.
Own technical design, delivery, reliability, security, and operational quality for your domains.
Work with Product, Design, Data, and other engineers to deliver customer value quickly and safely.
Improve engineering foundations, including test coverage, observability, CI/CD, performance, and developer experience.
Apply AI-assisted engineering tools responsibly while maintaining strong technical judgment.
Evaluate and build production AI capabilities where they are relevant to the product.
Review code, mentor engineers, and contribute to architecture and technical standards.