דרושים » הנדסה » Software Engineer, Product Engineering

we are seeking a Software Engineer to design, build, and scale the foundational systems infrastructure that powers products used by billions of people worldwide. In this role, you will work across the systems stack - spanning distributed systems, storage, networking, runtime environments, and platform services - to deliver reliable, high-performance infrastructure that enables product teams to move quickly and safely at scale. You will own technical design and execution across complex, cross-cutting systems projects, partnering closely with engineers across the organization to drive engineering excellence and long-term platform health.
Software Engineer, Systems Responsibilities
Design and implement scalable, reliable systems infrastructure components spanning distributed computing, storage, networking, or runtime environments
Own end-to-end technical design for systems-level projects, evaluating architectural trade-offs and driving decisions that balance performance, reliability, and maintainability
Instrument systems with telemetry, dashboards, and alerting to establish visibility into performance bottlenecks, reliability regressions, and failure modes
Lead incident response and root cause analysis for production systems issues, authoring retrospectives and driving follow-up improvements to prevent recurrence
Define and enforce service level objectives for owned systems, building debugging runbooks and mitigation playbooks to reduce mean time to resolution
Collaborate with cross-functional partners across product engineering, infrastructure, and security to ensure systems designs meet privacy, security, and integrity requirements
Drive engineering efficiency by identifying development bottlenecks, building internal tooling and automation, and completing migrations that eliminate legacy technical debt
Mentor other engineers on systems design principles, coding standards, and operational best practices, and contribute to recruiting and technical program efforts
Analyze performance profiles using instrumentation and profiling tools to identify hotspots and drive targeted optimizations across the systems stack
Communicate technical decisions, trade-offs, and project status clearly to stakeholders across engineering levels and cross-functional roles.

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.

we are seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
Machine Learning Engineer Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding.

Our Architecture Comando Team is looking for Software Engineers who are passionate about leading technology to the extreme.
What You'll Own:
Designing, developing, testing, deploying, and maintaining web applications using modern front-end and back-end technologies, including Node.js, React, TypeScript, JavaScript, and Python.
Leveraging AI-powered development tools such as Claude Code to accelerate development workflows, automate repetitive tasks, and improve code quality.
Leading server-side development using microservices architecture to ensure scalable and robust application performance.
Driving the design and implementation of micro frontend architecture, leveraging the industry's latest trends.
Mentoring junior and mid-level engineers through code reviews, pair programming, and technical guidance.
Collaborating with cross-functional teams, including product managers, designers, and other developers, to define technical direction and deliver high-quality applications.
Making architectural decisions and championing engineering best practices across the team.
Integrating AI and LLM capabilities into development pipelines and product features where applicable.

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 Amazon 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 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

Were looking for a senior engineer who is ready to move beyond traditional software development and take full ownership of product delivery.

This is not a classic backend engineering role. You will work directly with Product to turn ideas and requirements into production-ready solutions, make the technical decisions, and use AI coding agents as a core part of your engineering workflow.

You will own the outcome, not just the code. AI-generated code is your code, and you are accountable for its quality, security, performance, and maintainability.


What youll do
Own product features end-to-end, from requirements through production and monitoring.
Work with Product to translate business problems into clear technical solutions and execution plans.
Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations.
Use AI coding agents to accelerate implementation, testing, debugging, and automation.
Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability.
Make independent technical decisions and communicate architectural trade-offs clearly.
Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature.
Investigate and solve complex production and performance issues.
Continuously improve how we build, test, and ship software using AI-native development practices.