Software Engineer Ii Android Salary India in Canada

About the Role Sigma is transforming how businesses run by delivering a high performance platform on modern data architecture. Hence, we are growing the engineering team and looking for engineers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible for all users. What You Will Be Doing You will be responsible for developing elegant and responsive user experience using the latest front-end technologies. You'll own substantial pieces of the product, from design to launch Working with our product, UX design, and backend development teams, you will develop new features and technologies that make our product experience awesome and radically simplify the user experience for non-technical users You will leverage your technical expertise in front-end application development in the creation of novel visualizations for structured and unstructured data and develop new techniques for improving the performance and interactivity of the application Use modern frontend frameworks like React, GraphQL, TypeScript and Node.js Qualifications We Need 5+ years industry experience building and maintaining high-quality software An eye for great design and a passion for building products that provide a great user experience The ability to make the right trade-offs between functionality and delivery speed that supports delivering value to customers, all the while iterating based on feedback and roadmap priorities Desire to be a great teammate and have fun at work without compromising ownership towards your work Strong sense of craftsmanship, and a healthy academic curiosity to solve challenges at sigma Strong computer science fundamentals Qualifications We Want (also, skills you’ll learn!) Experience building software capabilities for analyzing large scale data web applications Prior exp

About the Role Sigma is transforming how businesses run by delivering a high performance platform on the modern data architecture. Hence, we are growing the engineering team and looking for engineers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible for all users. What You Will Be Doing Solve challenging problems that arise in providing an interactive experience on data warehouses for data exploration and analysis Build with modern tools and languages like Rust, Go, GraphQL, Node, and Kubernetes Build backend distributed services, new algorithms and modern API to support a cloud application Triage product or system issues and debug/track/resolve by analyzing the sources of issues Design and implement new software features to support our fast growing user base Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies Qualifications We Need 5+ years industry experience building and maintaining high-quality software Experience building and deploying robust and secure web applications in a continuous deployment environment Desire to be a great teammate and have fun at work without compromising ownership towards your work Strong sense of craftsmanship, and a healthy academic curiosity to solve challenges at sigma Strong Computer Science fundamentals Qualifications We Want (also, skills you’ll learn!) Data driven aptitude and its application to solve distributed system problems Data model design, and API development experience SQL query optimization and database internals Administered cloud service infrastructure (GCP, AWS, Azure) Prior experience working at high growth company solving technical problems to enable continued success Additional Job details The base salary range for this position is $170k - $240

Must be based in Vancouver The role We're hiring a dedicated data engineer to own the production data platform that our delivery, product, and engineering teams run on; designing integrated, governed data pipelines and delivering automated reporting, AI-assisted workflows, and predictive signals on top of them. You'll write production code, design systems, own CI/CD, and be accountable for the correctness of data that leaders make decisions on. What you'll do Design and operate our cloud data platform: ingestion, transformation, orchestration and serving. Integrate data from across the business (delivery tooling, CRM, product telemetry, finance, support and customer feedback systems) with shared identifiers, data contracts and lineage. Build automated and continuously refreshed reporting so teams manage by exception rather than chasing status. Connect approved AI agents to governed data with structured outputs, provenance, guardrails and human approval in the loop. Build feature pipelines and the MLOps controls behind predictive use cases: tests, versioning, promotion gates and drift monitoring. Own the engineering standards for data: testing, observability, environment promotion, PII classification and access control. What you'll bring Strong software engineering fundamentals: production-quality code, API and interface design, testing discipline, systems design. Real experience building and operating production data platforms on a cloud warehouse or lakehouse (Snowflake and AWS preferred) with dbt and a modern orchestrator. Practical AI tooling experience: something shipped, not prototyped. LLM-backed classification, extraction or structured-output pipelines; agent and tool-calling workflows; retrieval; evals. You can reaso

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 Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. 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

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo

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 Senior Software Engineer, you will lead 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: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. 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 contai

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), 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. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As a Staff Software Engineer, you’ll own the platformization roadmap for shared services, architecting a plan to decouple existing functionality into highly reusable services. Your impactful work helps improve Dialpad’s developer experience, productivity, security, and scalability. This position reports to our Senior D

About Clutch Clutch is Canada’s largest online used car retailer, delivering a seamless, hassle-free car-buying experience to drivers everywhere. Customers can browse hundreds of cars from the comfort of their home, get the right one delivered to their door, and enjoy peace of mind with our 10-Day Money-Back Guarantee. Named one of Canada’s Top Growing Companies two years in a row and awarded a spot on LinkedIn’s Top Canadian Startups list, we’re looking to add curious, hard-working, and driven individuals to our growing team. Headquartered in Toronto, Clutch was founded in 2017. Clutch is backed by world-class investors including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca About the role At Clutch, we believe advances in AI are fundamentally changing how great products are built. Traditional handoffs between product, design, and engineering are giving way to smaller, faster teams where builders can take ideas from concept to production in days instead of months. Our engineers don't just write code, they own outcomes. That means working directly with stakeholders to understand the problem, shaping the solution, thinking through design and user experience, and building scalable products end to end, using strong engineering principles and AI-powered development tools. We're looking for people who see a broken process or an unanswered question and feel compelled to fix it, not wait for it to land in their queue. This is a role for people who thrive on ownership of the problem, the solution, and the outcome. You'll have the autonomy to take initiatives from idea to launch, using whatever tools the job requires (code, AI, prototypes, judgment) to get there. If you're energized by ambiguity, moving fast, and building products with real business impact, you'll thrive at Clutch. Technology at Clutch We believe great engineers can learn great technology. Our team builds with technologies like TypeScript, React, Express, Postgr

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 running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role 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 Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec