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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, ML Feature Store - **Company:** Snap Inc. - **Location:** Palo Alto, CA, United States - **Experience:** Expert - **Salary:** $229,000.0 - $343,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Computing Platforms, C++ (Programming Language), Cloud Computing, Software Design Patterns, Distributed Systems, Python (Programming Language), Performance Tuning, Service-Oriented Architecture, Software Engineering, Backend, Information Technology, Codebase, Machine Learning Operations, C++14, Data Pipelines, Golang, Microservices - **Published:** July 19, 2026 - **Apply:** https://dejobs.org/x/x/9B210071E44A4F6AB690A9EA2B33912A/job/ ## About the Role * Deep experience designing, building and operating backend services or distributed systems at significant scale. * Strong technical leadership skills, with the ability to set vision, ideate high-impact projects and translate strategy into executable roadmaps. * Proven ability to lead complex, cross-functional initiatives over multiple quarters while balancing architectural quality, reliability and delivery velocity. * Strong foundation in system design, including APIs, service architecture, compute platforms, storage concepts, observability and workflow orchestration. * Proven track record of owning highly available, mission-critical systems, including operational readiness, incident response and systemic improvements. * Strong judgment in making technical trade-offs and prioritizing the right long-term platform investments for a large engineering organization. * Excellent collaboration and communication skills, with the ability to influence engineers and leaders across Senior Manager- or Director-level organizations. * Ability to mentor, unblock and elevate other engineers while creating structures and mechanisms that make teams more effective over time. * Comfort operating in ambiguity and driving clarity in technically complex problem spaces. * Familiarity with responsible use of emerging AI technologies to improve engineering quality, alignment and innovation at scale., * Bachelor's degree in a technical field such as Computer Science or equivalent practical experience * 9+ years of software development experience; or Master's degree with 8+ years of experience; or PhD with 5+ years of experience * Experience as a technical lead, domain expert or owner of complex technical initiatives * Experience building large scale storage, backend or distributed systems, * Deep expertise in modern C++ (C++11/14/17), with experience in large-scale production codebases * Experience with C++, Go, Java, Python or similar backend languages. * Experience with large-scale microservices, cloud infrastructure and/or platform architecture * Proficiency with performance optimization techniques * Experience building or scaling ML Infrastructure systems and/or real-time data pipelines * Strong CS fundamentals (algorithms and data structures) and problem-solving skills * Comfortable working in a fast-paced, iterative and highly collaborative environment * Knowledge of software design patterns and best practices ## Description * Serve features reliably for large-scale batch inference and low-latency online inference, maintaining consistency across serving paths and meeting latency and freshness requirements of production models. * Maintain features in a centralized, versioned feature registry, ensuring definitions are discoverable, well-documented and reusable across teams and models so common logic is defined once rather than duplicated. * Design and manage feature storage solutions for correctness, freshness and efficient retrieval, selecting appropriate storage patterns for training-scale reads and low-latency serving lookups. * Build scalable, distributed systems with attention to compute and storage efficiency, backed by monitoring, alerting, and sound operational practices that keep feature serving systems reliable and maintainable in production. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Scoring 2000 Products per Request: Performance Pitfalls in Golang](https://www.wearedevelopers.com/videos/2073-scoring-2000-products-per-request-performance-pitfalls-in-golang) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)