Software Engineer 3 App Analysis Modelling Salary India in San Francisco

About the Role Sigma Computing is redefining business intelligence by making complex data analysis accessible through a high-performance platform built for the modern data stack. The Compiler Team plays a foundational role in this mission by transforming user-driven spreadsheet interactions into highly optimized SQL queries, enabling seamless exploratory analytics on cloud data warehouses. As a member of the Compiler Team, you will join a group of engineers dedicated to building the core systems and abstractions that power Sigma’s intuitive spreadsheet interface, ensuring speed, reliability, and scalability for all users. What You Will Be Doing Tackle core challenges at the intersection of data modeling, query compilation, and large-scale interactive analytics—making it possible for end-users to query data warehouses efficiently without deep technical knowledge Design, build, and maintain sophisticated compiler infrastructure and intermediate representations that translate spreadsheet operations into optimized query plans Apply advanced optimization strategies to improve performance and accuracy across a wide range of query workloads and data architectures Contribute to both backend (Rust) and key frontend foundations (TypeScript), evolving critical abstractions that enable end-to-end workflow optimizations and new features Debug, analyze, and resolve complex issues, ensuring robustness and maintainability in a rapidly evolving product Collaborate with engineers and product stakeholders to review designs and code, driving technical best practices and architectural decisions throughout the team and company Qualifications We Need 5+ years experience engineering high-quality software systems Demonstrated success building and maintaining complex infrastructure or core platform services Deep understanding of Computer Science fundamentals, particularly in compilers, algorithms, SQL Optimization Passion for teamwork, technical ownership, and continually

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web develo

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components. Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Prof

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

About the Team Come help us build and develop tools serving hundreds of engineers internally! We’re looking for a Fullstack Software Engineer to join our Developer Insights team. About the Role Our mission is to improve the developer experience of engineers at DoorDash by building various internal products, including our internal developer portal, Developer Insights. Our success as a platform team depends on the success of the product teams we serve. Because of this, we invest in building a strong community that encourages participation and promotes best practices. You’re excited about this opportunity because you will… Introduce cutting edge technologies to our engineering organization, including tools built on LLMs Build new features for Developer Insights (using Backstage.io) Improve the developer experience for all of our engineers Work and collaborate across team boundaries. Contribute features and bug fixes to upstream open-source projects. Mentor and educate your peers. Lead the team in a technical fashion and assist in roadmap planning and measurement of existing features. Represent the team at large in OKR and engineering all-hands presentations. Context switch from frontend to backend to data depending on the need that arises. We’re excited about you because… You have at least 2 years of experience in web technologies using Typescript with React on the frontend with Java, Kotlin, Python or Go backend experience. You have a product mindset and apply that to how you would build out platform services. You love systems and software, and you're proficient in both. You’re curious and dive deep into different system architectures. You are an organized and excellent written and verbal communicator. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Compensation The successful candidate’s starti

About the Team The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Caching team owns every caching offering at DoorDash end to end, including ElastiCache (Redis/Valkey), Boulder (our KVRocks-based key-value store for high-QPS feature serving), Entity Cache (read Bill Shen’s engineering blog post, “ High-Performance Proxy Cache for DoorDash Services ”), and the Distributed Lock Service, plus the smart clients (asgard-redis, valkey-go) that sit in front of them. These systems back critical product surfaces across DoorDash, Wolt, and Deliveroo: the team runs roughly 400 ElastiCache clusters serving hundreds of millions of GET requests per second in aggregate, and Boulder, our offline-to-online feature store, serves billions of feature lookups per second at peak. About the Role The team owns provisioning of clusters and the smart clients that sit in front of them, baking in sensible defaults so that other engineering teams get a turnkey caching solution instead of having to run their own. You'll help drive Boulder's evolution to scale further, improve cost efficiency, enhance performance, and support real-time updates; re-platform the Distributed Lock Service onto a strongly consistent backend; and build the self-serve tooling and recommendation engine that let customers describe a workload (QPS, TTL, payload size, latency profile) and get the right backend without talking to a human. You'll go deep on cache invalidation, replication, sharding, compaction, and failover, while shipping the guardrails, automation, and observability that keep this scale operable by a small team. You must be located in San Francisco, Seattle, or the New York Metro Area for this hybrid position. You will report to the Engineering Manager on the Distributed Caching team within the Storage organization. You’re excited about this opportunity b

About the Team The Code Quality team sits within the Developer Platform organization and owns the systems that keep DoorDash's codebase healthy and secure as it scales: static analysis, quality gates, test frameworks, regression infrastructure, and tooling. Our job is to make sure the signals engineers rely on before shipping — test results, coverage, performance feedback etc — are fast and trustworthy. The decisions we make about tooling and standards directly shape how confidently and quickly engineering teams at DoorDash can ship to production. About the Role We're looking for Software Engineers to help build and maintain the systems that validate code quality across DoorDash's engineering org, treating our tooling as a critical product for the engineers who rely on it every day: static analysis and quality gates, test frameworks and regression infrastructure. You’ll design the tooling and automation that will help derive trustworthy quality signals, integrate them into the development lifecycle, and make it easy for engineers to execute reliable, repeatable workflows. You will collaborate across the engineering org, partnering directly with the teams who use what you build to understand the accuracy, reliability and performance of their functionality. You will report into the Engineering Manager on our Code Quality team in our Developer Platform organization. You must be located in either San Francisco, CA, Sunnyvale, CA, Los Angeles, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Build and maintain quality tooling — static analysis, quality gates, coverage reporting, test frameworks, regression infrastructure — and integrate it directly into our developer workflows and CI/CD pipelines Define and derive quality signals - flakiness, pass rate, coverage, performance, scale readiness etc - Build tooling that improves everyday engineering workflows, including local development, CI/CD, debugging, and rollou

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

About the Team Our mission is to provide a world-class development experience that makes DoorDash's web engineers among the most productive in the industry. We achieve this by creating the tools that enable all teams at the company to ship features quickly and reliably. Because their success is our success, we are deeply invested in building a strong, collaborative web community that champions best practices and welcomes participation. About the Role As a Software Engineer on the Developer Experience team, you will build the foundational pieces for all DoorDash, Wolt and Deliveroo Web applications. These include monorepos, build & CI systems and agent-first development tooling. You will work closely with engineers and other internal stakeholders to deliver large and impactful initiatives. Additionally, you will be a culture carrier for our Web engineers through mentorship, education, and engagement of your peers. You will report into the Engineering Manager of our Web Developer Experience team in our Developer Platform organization. You must be located in either San Francisco, CA, Sunnyvale, CA, Los Angeles, CA, Seattle, WA, or New York, NY. You’re excited about this opportunity because you will… Shape the future of Web Development. You will have a direct and meaningful impact on the daily workflows of every web engineer at the company, enhancing their productivity and overall developer experience. Build from the ground up. You will architect and implement foundational libraries, cutting-edge build systems, and innovative development tools that serve as the bedrock for all of our web applications. Solve complex, high-impact challenges. You will tackle some of the most significant technical hurdles in web engineering, and the solutions you deliver will be leveraged by hundreds of employees across numerous product teams. Act as a force multiplier. Your work will directly empower product teams to build, test, and release new features to our customers fa

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We're hiring a Robotics Infrastructure Engineer in our Autonomy Software team. In this role, you'll own, build, and manage the infrastructure that makes aerial autonomy development possible. You'll work on the onboard systems that keep a drone alive (process management, health monitoring, parameterization) and the development environment that makes the team fast (build systems, CI/CD, logging, debugging, regression testing). This is not cloud infrastructure. This is real-time, fault-tolerant, onboard software for vehicles that cannot gracefully restart at 50 meters altitude. You're excited about this opportunity because you will… Play an integral role on a small and focused team Develop and own critical onboard components: process management, health monitoring, configuration management, and message passing Own the build system (C++, Python) and middleware layer (ROS2), including cross-compilation for Jetson targets Design and maintain CI/CD pipelines and regression testing infrastructure Build and manage the parameterization system, including schema definition, validation, migration, and deployment Build robotics logging, plotting, and debugging tools that make the entire team more productive Work closely with the simulation team to support SIL/HIL development workflows Define reliability standards for onboard software: watchdogs, failover, and graceful degradation We're excited about you because… You have prior experience at a robotics company in a similar infrastructure role You have experience with robotics middleware (ROS2, LCM, eCal, Apex.AI) You have experience with build systems and package managers (CMake, Bazel, Nix, Conan) You have experience with NVidia Jetson and Je

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos