Careers at Swiggy

Key Responsibilities Develop and maintain React Native applications for iOS and Android, ensuring optimal performance and responsiveness. Implement app performance optimizations (reducing app size, improving load times, and memory management). Debug, troubleshoot, and improve application stability. Write unit and integration tests using React Native/React Testing Library to ensure app reliability. Collaborate with designers, product managers, and backend engineers to deliver seamless user experiences. Integrate APIs, third-party SDKs, and state management solutions like Redux, Zustand, Recoil, or Context API. Ensure best practices in code architecture, security, and scalability. Hands-on experience with AI-assisted development tools (Claude, GitHub Copilot, Codeium, Codex,Cursor etc.) and understanding of their strengths, limitations, and best practices for maximizing productivity Core Technical Skills Expert proficiency in React and TypeScript — strong understanding of hooks, state management patterns, and TypeScript best practices Understanding of RN framework and familiarity of Native modules. Deep expertise in Next.js — including Server-Side Rendering (SSR), Incremental Static Regeneration (ISR), API routes, middleware, optimization strategies, and the new App Router paradigm Good understanding of ES6+, async/await, functional programming patterns, and modern JavaScript practices Proficiency in modern CSS — Tailwind CSS, CSS modules, CSS-in-JS solutions (Emotion, Styled Components), and responsive design principles Hands-on experience with modern build tools — Webpack, Vite, ESBuild, or equivalent bundlers; understanding of tree-shaking, code splitting, and lazy loading Good foundation in Git and collaborative development workflows Working knowledge of Node.js and backend fundamentals — enough to understand API design, authentication, and server-side implications System Design & Architecture Ability to design scalable, maintainable component architectures and design systems Understanding of state management solutions (Redux, Zustand, Context API) and when to use each Knowledge of micro-frontends, module federation, and how to structure large applications Experience with component composition, prop drilling solutions, and reusable library design Understanding of multi app strategy, Android AAB, Metric config, Build Pipelines etc Performance & Monitoring Experience with app performance optimization (profiling, Crash rate, ANR, cold & hot boot load times, reducing memory usage, minimizing bundle size). Deep understanding of frontend performance metrics (Core Web Vitals, FCP, LCP, CLS, FID) and optimization techniques Knowledge of monitoring, observability, and error tracking solutions (Newrelic, Sentry, DataDog, etc.) Understanding of lazy loading, code splitting, image optimization, and caching strategies Quality & Best Practices Experience in testing frameworks — Jest, RN / React Testing Library, Vitest, E2E testing (Maestro, Cypress, Playwright) Sound knowledge of design patterns, SOLID principles, and writing clean, maintainable code Understanding of web accessibility (WCAG standards, semantic HTML, ARIA attributes) and experience implementing accessible UIs Proficiency in browser compatibility and cross-browser testing Exposure to code quality tools — ESLint, Prettier, Husky, pre-commit hooks, automated CI/CD pipelines Nice to Have Skills Experience with performance profiling tools (Chrome DevTools, Lighthouse, WebPageTest) and real-world optimization strategies Prior experience with App Store & Google Play Store deployment processes. Knowledge of Firebase services, push notifications, deep linking, and analytics. Experience with React Native upgrades and handling breaking changes. Experience working with native modules (Objective-C, Swift, Java, Kotlin). Hands-on experience with CI/CD pipelines (Bitrise, GitHub Actions, or similar). Experience with headless CMS, GraphQL, or API integration layers Knowledge of SEO best practices for SPA and Next.js applications Familiarity with Storybook, design tokens, and component documentation Experience with DevOps basics — Docker, CI/CD pipelines, environment management Understanding of animation libraries (Framer Motion, React Spring) and interactive UX Exposure to AI /LLM integrations in frontend (streaming, chunking, prompt optimization) B Tech/M Tech in Computer Science or equivalent from a reputed college with 1-3 years of experience in a product development company (strong internship/project experience considered). Visit our tech blogs to learn more about some the challenges we deal with: https://bytes.swiggy.com/the-swiggy-delivery-challenge-part-one-6a2abb4f82f6 https://bytes.swiggy.com/swiggy-distance-service-9868dcf613f4 https://bytes.swiggy.com/the-tech-that-brings-you-your-food-1a7926229886 Visit our tech blogs to learn more about some the challenges we deal with: https://medium.com/swiggy-bytes We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

Software Development Engineer III — Backend, Trust & Safety Location: Bangalore Experience: 6 – 8 years About the team and the role What we do — Trust & Safety keeps Swiggy safe on both sides: the platform stays safe for our consumers, and the platform and our businesses stay protected from fraudsters and bad actors. What we build — the real-time risk decisioning platform that sits in the critical path of Swiggy's consumer journeys, detecting and acting on fraud and abuse as it happens, across all of our consumer businesses. Stack — low-latency Go microservices, gRPC, event streams, NoSQL stores, caching and AWS, with Python and our data platform powering offline analysis and ML-based risk models. Why it's hard — every decision is a two-sided bet. Act too aggressively and we hurt genuine customers; act too little and the business leaks money. And the call has to be made in milliseconds. The adversary adapts — patterns that worked last quarter stop working, so the platform has to let risk and business teams respond quickly rather than wait on an engineering cycle. Your charter — own architectural decisions end-to-end, lead projects independently, mentor engineers, and partner with product, analytics and business teams to translate risk and customer-experience goals into scalable, production-grade solutions. AI-native by design — we are looking for an engineer who has already put AI systems into production at scale, who builds agentic automations to remove friction for the teams around them, and who can point AI at our own systems at scale to find where they break before an attacker does. If that is how you already work, you will have a lot of room to run here. What will you get to do here? Technical leadership Create architectures and designs for new solutions across existing and new areas Decide technology and tool choices for your team, and be responsible for them Drive the long-term technology vision for the team Lead code reviews, design reviews and architecture discussions, and drive engineering best practices Experiment with new and relevant technologies, driving adoption while measuring yourself on the impact you create Mentor engineers and raise the overall engineering bar Building the platform Design low-latency distributed systems that make real-time risk decisions in the critical path at Swiggy scale Architect the signal and feature platform — streaming and batch aggregations, entity-level risk features, served within tight latency budgets Make the platform increasingly self-serve, so risk and business teams can ship new checks and policies without an engineering deploy Build detection for emerging abuse patterns — entity linkage, velocity and anomaly detection, and ML risk scores wired into live decisioning Own the business outcome: measure risk exposure against false-positive impact, and build the experimentation and backtesting tooling to prove a change before it goes live Own reliability in a critical-path service — instrumentation, observability, graceful degradation, and designing for scale from day one What qualities are we looking for? Engineering fundamentals B.Tech / M.Tech in Computer Science or equivalent from a reputed college, with 6 – 8 years of experience in a product development company Sound knowledge and application of algorithms and data structures, with space and time complexities Proficiency in Go or Python (ideally both) Follows industry coding standards, writing maintainable, scalable and efficient code to solve business problems Systems and scale Strong experience building and operating distributed systems — message queues, event-driven architectures, stream processing, caching, async processing Solid system design skills, comfortable owning end-to-end architecture Experience building latency-sensitive services in a transactional critical path — p99s, timeouts, circuit breaking, fallback behavior Experience with NoSQL databases, Kafka or similar streaming systems, and AWS Comfort working with data — SQL on a warehouse / data lake, building metrics, and reasoning about decisions from production data rather than intuition Leadership Demonstrated ability to lead projects independently from design to production Track record of mentoring engineers and elevating team capabilities What "AI-native" means for this role Has productionised AI solutions at scale, not just prototypes Builds automations for real user workflows — spotting where people lose time to manual, repetitive steps and engineering that friction away Hands-on with open-weight models such as Qwen or GLM to build task-specific SLMs using few-shot prompting Proven experience in loop engineering and quality gates — designing the agentic loops, evals and automated checks that make AI output trustworthy enough to ship Can break a system using AI at scale — adversarial testing as a first instinct Active user of AI coding tools (Claude, Copilot, Cursor) in day-to-day engineering Worked on trust & safety, fraud, risk or payments systems, with an instinct for how legitimate flows get exploited (ethical hacking exposure is a plus) Experience with rule engines, policy / decisioning platforms, or configuration-driven systems built for non-engineering users Hands-on experience productionising ML — feature stores, real-time model serving, model monitoring Exposure to graph-based detection (entity resolution, linkage analysis) or anomaly detection at scale Visit our tech blogs to learn more about some of the challenges we deal with: https://bytes.swiggy.com/smart-select-tailored-cart-suggestions-38267fdca12b https://bytes.swiggy.com/automating-mobile-event-verification-1d840f39d300 https://bytes.swiggy.com/improving-video-cache-hits-on-swiggy-apps-610f395fff46 https://bytes.swiggy.com/a-deep-dive-into-dynamic-widget-swiggys-server-driven-ui-system-92cdc3b16ec6 https://bytes.swiggy.com/building-a-robust-mobile-platform-team-2ee40cce8670 Media on Swiggy’s Mobile Apps. Swiggy believes that a seamless and… | by Vignesh Muralidharan | Swiggy Bytes — Tech Blog https://bytes.swiggy.com/swiggy-design-language-system-1ef9cca11186 https://bytes.swiggy.com/gradle-incremental-test-runner-125cee1e68a7 https://bytes.swiggy.com/swiss-knife-that-powers-the-swiggy-app-dff9dc49a580 We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

What will you get to do here? Design, develop, and deploy scalable optimization algorithms for supply chain, assortment planning etc. Translate business problems into mathematical formulations using tools like Linear Programming, Integer Programming, and Heuristics. Build and improve predictive models using ML techniques (regression, classification, time-series forecasting). Collaborate closely with Product, Engineering, and Operations teams to take models from prototype to production. Analyze model performance and continuously iterate to improve accuracy and efficiency. Drive measurable impact on key business metrics such as availability, wastage, revenue per order, cost per order etcWork on high-impact, real-world problems at massive scale. Be a part of a fast-growing vertical within Swiggy with opportunities to innovate and experiment. Collaborate with a world-class team of engineers, product managers, and data scientists. Competitive compensation and a culture that promotes learning, ownership, and growth. What qualities are we looking for? 5+ years of experience in Data Science or Applied Research roles. Strong foundation in Operations Research and Mathematical Optimization (e.g., LP, MILP, ILP). Solid hands-on experience with Python, SQL, and at least one optimization solver (e.g., Gurobi, OR-Tools, CPLEX). Good understanding of Machine Learning concepts and frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). Experience in solving large-scale real-world problems using a combination of ML and OR techniques. Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. Excellent communication and stakeholder management skills. Experience in supply chain, logistics, food delivery, or q-commerce/e-commerce domains. Prior experience in building real-time or near real-time decision systems. Experience working with large datasets and distributed systems (e.g., Spark). Few requirements I would like to add : Strong understanding of statistical techniques. Distributions and loss functions. Production level coding standards and not just POC. Understanding of cache layers, database schema designs, abstractions and modularity Experience designing or working with agentic/autonomous decision systems that incorporate human-in-the-loop review, exception handling, or override mechanisms. 5+ years of experience in Data Science or Applied Research roles. Strong foundation in Operations Research and Mathematical Optimization (e.g., LP, MILP, ILP). Solid hands-on experience with Python, SQL, and at least one optimization solver (e.g., Gurobi, OR-Tools, CPLEX) Visit our tech blogs to learn more about some the challenges we deal with: https://bytes.swiggy.com/the-swiggy-delivery-challenge-part-one-6a2abb4f82f6 https://bytes.swiggy.com/how-ai-at-swiggy-is-transforming-convenience-eae0a32055ae https://bytes.swiggy.com/decoding-food-intelligence-at-swiggy-5011e21dbc86 We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

About the Role As a Staff Data Scientist, you will architect and lead efficient solutions across key domains such as Recommendation, Search, Ads, and Discount Optimization. You will mentor cross-functional teams, review technical architectures and maintain a high standard for holistic solution design. Driving innovation, you will foster a culture of adopting (SOTA) models. Leveraging deep expertise in ML, DL and advancements like GenAI/LLMs, you will guide teams in acquiring new skills and integrating evolving paradigms into production systems. You will operate as a senior technical leader for the Food charter: shaping problem formulation, influencing product roadmaps, and ensuring our AI systems are robust, low-latency, and business-outcome driven What You’ll Do Own and drive the technical roadmap for AI systems across Search, Recommendations, Ads and Discounting, from problem framing to production rollout and post-launch iteration. Architect end-to-end ML/AI pipelines (data, models, orchestration, evaluation, monitoring) that meet strict constraints on latency, scale, cost and reliability. Evaluate and introduce SOTA techniques (retrieval/ranking, bandits/RL, causal uplift, GenAI/agents) in a pragmatic, production-ready manner. Partner with Product and Business to define success metrics, set up robust experimentation, and tie AI investments clearly to business KPIs and ROI. Provide architectural and design reviews for high-stakes ML systems across the Food charter; set and enforce engineering and MLOps best practices. Mentor and uplevel Senior/Lead Data Scientists and MLEs; act as a thought partner to leadership on build-vs-buy, platform strategy and multi-year bets. Represent Swiggy AI in internal and external forums (tech talks, blogs, publications, conferences) and help build the brand for Food AI. Skills & Experience Core Technical Skills Deep expertise in classical ML, representation learning and modern deep learning (e.g., transformers, two-tower/rec models, ranking architectures). Search & Recommendations : large-scale retrieval, LTR, multi-stage ranking, vector search, multi objective ranking and personalization.Fine-tuning SLMs/LLMs, building RAG/agentic workflows, conversational or copilot-style systems. Ads & Discounting : Bandits/RL for allocation, uplift/causal models, constrained optimization for budgets/pricing. Risk/Fraud: graph-based models (e.g., entity graphs, GNNs for fraud rings), classical ML (GBMs, tree ensembles, logistic regression), and deep learning frameworks such as PyTorch/TensorFlow, with hands-on work on encoder/transformer architectures (SLMs, BERT-style models) for representation learning, feature extraction and risk scoring in real-time systems Hands-on experience with: Strong system design skills for low-latency, high-throughput ML platforms; fluency with Python, PySpark, PyTorch/TensorFlow, feature stores, vector DBs and modern MLOps. Architectural & Strategic Skills Ability to design AI-first systems end-to-end: data contracts, feature pipelines, serving architecture, feedback loops and continuous learning. Comfort evaluating open-source vs proprietary models/tools, with clear reasoning on cost, risk, scalability and maintainability. Experience with orchestration / agent frameworks (e.g., LangGraph, CrewAI, AutoGen) and concepts like ontology layers, graph knowledge bases and multi-agent workflows. Strong product thinking: can connect model capabilities to customer journeys and business KPIs, and influence roadmaps accordingly. Leadership & Collaboration Demonstrated experience as a tech lead / staff-level IC, influencing multiple pods or domains. Ability to mentor and coach senior DS/MLEs, drive technical standards, and create a high-bar culture for experimentation and measurement. Excellent written and verbal communication; can simplify complex ideas for non-experts and build alignment across Product, Engineering and Business stakeholders. Bias for action, ownership and comfort working in an ambiguous, fast-paced environment. Why Join Swiggy? Opportunity to work on impactful and challenging projects in the AI domain. Chance to build innovative solutions at scale, directly impacting millions of users. Collaborative work culture fostering learning, growth, and innovation . 8–12 years of experience in AI/Data Science, with a strong track record of shipping and scaling ML/DL systems in production. Visit our tech blogs to learn more about some of the challenges we deal with: The Swiggy Delivery Challenge Part One How AI at Swiggy is Transforming Convenience Decoding Food Intelligence at Swiggy We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.

What qualities are we looking for? Expert proficiency in React and TypeScript — strong understanding of hooks, state management patterns, and TypeScript best practices Deep expertise in Next.js — including Server-Side Rendering (SSR), Incremental Static Regeneration (ISR), API routes, middleware, optimization strategies Solid understanding of ES6+, async/await, functional programming patterns, and modern JavaScript practices Proficiency in modern CSS — Tailwind CSS, CSS modules, CSS-in-JS solutions (Emotion, Styled Components), and responsive design principles Hands-on experience with modern build tools — Webpack, Vite, ESBuild, or equivalent bundlers; understanding of tree-shaking, code splitting, and lazy loading Strong knowledge of CI/CD pipelines, deployment strategies, and automation — experience with tools like GitHub Actions, GitLab CI, Jenkins, or similar platforms Strong foundation in Git and collaborative development workflows Working knowledge of Node.js and backend fundamentals — enough to understand API design, authentication, and server-side implications System Design & Architecture: Ability to design scalable, maintainable component architectures and design systems Understanding of state management solutions (Redux, Zustand, Context API) and when to use each Knowledge of micro-frontends, module federation, and how to structure large applications Experience with component composition, prop drilling solutions, and reusable library design Performance & Monitoring: Deep understanding of frontend performance metrics (Core Web Vitals, FCP, LCP, CLS, FID) and optimization techniques Experience with performance profiling tools (Chrome DevTools, Lighthouse, WebPageTest) and real-world optimization strategies Knowledge of monitoring, observability, and error tracking solutions (Sentry, DataDog, etc.) Understanding of lazy loading, code splitting, image optimization, and caching strategies Quality & Best Practices: Expertise in testing frameworks — Jest, React Testing Library, Vitest, E2E testing (Cypress, Playwright) Sound knowledge of design patterns, SOLID principles, and writing clean, maintainable code Understanding of web accessibility (WCAG standards, semantic HTML, ARIA attributes) and experience implementing accessible UIs Proficiency in browser compatibility and cross-browser testing Exposure to code quality tools — ESLint, Prettier, Husky, pre-commit hooks, automated CI/CD pipelines Nice-to-Have Skills: Experience with headless CMS, GraphQL, or API integration layers Knowledge of SEO best practices for SPA and Next.js applications Familiarity with Storybook, design tokens, and component documentation Understanding of animation libraries (Framer Motion, React Spring) and interactive UX Exposure to AI/LLM integrations in frontend (streaming, chunking, prompt optimization) Experience working with WebViews, React Native, or other hybrid mobile technologies — understanding of bridge communication, native module integration, and platform-specific constraints Hands-on experience with AI-assisted development tools (Claude, GitHub Copilot, Codeium, Codex,Cursor etc.) and understanding of their strengths, limitations, and best practices for maximizing productivity Key Responsibilities Own end-to-end design and architecture of complex frontend features, translating product requirements into technical specifications Develop high-performance, production-ready React and Next.js applications with pixel-perfect UI implementations Drive performance optimization initiatives — identify bottlenecks, implement improvements, and establish monitoring to track metrics Build and maintain reusable component libraries, design systems, and utility functions for team-wide adoption Ensure technical feasibility of UI/UX designs and work closely with designers to balance aesthetics with performance and accessibility Champion best practices in code quality, testing, accessibility, and maintainability across the team Lead adoption of AI-assisted development tools (Claude, GitHub Copilot, etc.) within the team — evaluate effectiveness, establish best practices, and mentor others on productivity gains Mentor junior engineers and conduct thorough code reviews to foster a culture of excellence Stay current with frontend ecosystem trends, emerging AI tools, and new frameworks/patterns — evaluate and advocate for adoption Collaborate with backend and DevOps teams to understand API contracts, optimize data fetching, and streamline deployment pipelines Debug and optimize third-party library usage, understanding their internals and identifying performance trade-offs Participate in system design discussions and contribute to architectural decisions at the team and platform level What You'll Get Work with a modern, constantly evolving tech stack — React, TypeScript, Next.js, and cutting-edge frontend tooling Opportunity to own significant parts of the Swiggy platform impacting millions of users Mentorship and growth — partner with experienced engineers and lead technical initiatives Impact across teams — collaborate with product, design, mobile, and backend teams on high-impact projects Competitive compensation, benefits, and growth opportunities within a thriving tech company B Tech/M Tech in Computer Science or equivalent from a reputed college with minimum 3 – 5 years of experience in product development company. Visit our tech blogs to learn more about some the challenges we deal with: https://bytes.swiggy.com/the-swiggy-delivery-challenge-part-one-6a2abb4f82f6 https://bytes.swiggy.com/swiggy-distance-service-9868dcf613f4 https://bytes.swiggy.com/the-tech-that-brings-you-your-food-1a7926229886 We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.