Design Engineer in Singapore

Senior/Engineer, NAND Wafer Level Reliability & Design — Fab 10N/X, Singapore. Apply via Workday.

ENGINEER, NAND SILICON DESIGN VALIDATION — MSB, Singapore. Apply via Workday.

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Database Operations is responsible for the deployment and maintenance of the database layer that Palantir’s products depend on. As an engineer on the Database Operations team, you will design how databases are deployed and operated across a wide variety of environments, build the automation and observability that keep them healthy, and respond to the critical production issues that affect some of the world's most impactful use cases.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Payments is Stripe's flagship product. Our payments platform processes trillions of dollars annually. This team has the opportunity to expand the reach of Stripe's global payments network, design and implement novel payment capabilities, and deliver best-in-class reliability and performance. We have software engineers in almost every team across Stripe, and in this role, you'll be making some of the most significant decisions for the company. You'll get to work with other engineers to build features that span various parts of the system, as well as our business, sales, and operations teams to understand and solve our users' pain points. What you'll do You'll work on projects that span technologies, systems, and processes where you'll design, build, test, and ship great code every day. Responsibilities Design, build, and maintain APIs, services, and systems across Stripe's engineering teams Work with a wide range of systems, processes, and technologies to own and solve problems end-to-end Collaborate with other engineering teams across Stripe's global offices Uphold our high engineering standards and bring consistency to the many codebases and processes you encounter Improve engineering standards, tooling, and processes Who you are You're energized by solving real problems for real users. You use the word "users" or "customers" a million times a day. You thrive at the intersection of technology and business—equally comfortable diving deep int

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Sales Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the APJ region. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, incl

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and de

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Software Engineer, Data Layer As a Software Engineer on the Data Layer team within the Platform group, you'll shape the API (GraphQL) platform that connects every client application to Coinbase's backend services, handling the majority of user traffic across Consumer, Base, and Institutional products. You'll own the critical systems that route and serve API requests at scale, improving reliability, performance, and developer experience for hundreds of engineers building on this foundation layer. What you'll do: Own and deliver projects end to end, from scoping and system design through implementation, rollout, and production validation, driving measurable progress on the team's highest-priority initiatives. Design and build high-reliability, low-latency systems serving millions of users, tackling challenges like caching, upstream service optimization, and efficient connection management at scale. Build and improve the API framework and tooling that hundreds of engineers depend on, making it fast and easy for teams across the company to build, test, and ship independently. Drive operational excellence across T0 services: own SLOs, improve observability, lead incident response, and reduce operational toil so the team can invest in high-leverage work. Partner cross-functionally with product engineering teams to design API schemas, support service launches, and ens

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Ads Solutions team partners closely with advertisers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform—while maintaining strong standards for user trust and platform integrity. About the Role We’re looking for an Ads Solutions Engineer to partner with advertisers and agencies throughout the pre-sales and growth lifecycle, helping them successfully evaluate, launch, and scale on OpenAI’s advertising platform. You will serve as the technical expert in the sales process, translating advertiser objectives into scalable technical solutions across measurement, integrations, data activation, and campaign execution. This role sits at the intersection of sales, product, and engineering. You’ll work closely with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams to remove technical blockers, accelerate revenue growth, and shape the future of OpenAI’s ads platform. In this role, you will: Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure. Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals. Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks. Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution, audience signals, and reporting. Troubleshoot technical issues related to implementation, signal quality, delivery, and measurement performance. Build compelling demos, proofs of concept, and technical narratives that demonstrate

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for an Applied AI Engineer, Cyber to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Singapore office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workflow

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected. In this role you will Own technical delivery across multiple deployments from first prototype to stable production. Build full-stack systems that deliver customer value and sharpen how we learn. Embed closely with customer teams, understand their needs, and guide adoption of what you build. Scope work, sequence delivery, and remove blockers early. Make trade-offs between scope, speed, and quality; adjust plans to protect delivery. Contribute directly in the code when progress or clarity depends on it. Codify working patterns into tools, playbooks, or building blocks that others can use. Share field feedback that helps Research and Product understand where the models succeed and where they can improve. Keep teams moving through clarity and follow-through. You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work. Have scoped and delivered complex systems in fast-moving or ambiguous environments. Write and review production-grade code across frontend and backend using P

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. 5 Work Days Per Week Office at Tai Seng Exchange Tower B Near Tai Seng MRT, Singapore Insurance Coverage Entitled to Yearly Bonus & Performance Bonus Responsibilities (Site Reliability Engineer - Senior / Lead ) High Availability and Stability Maintenance of Application Systems: Includes daily monitoring, alert response, emergency handling, on-call duties, regular system health checks, and performance optimization. Compliance and Secure Access Construction for Application Systems: Ensure operational design, processes, and data management comply with relevant privacy and data protection laws. Ensure compliance with full auditing and regulatory checks and provide auditing materials as required. Change and Release Management: Best practices for application system changes, including change control, version management, and rollback strategies, while ensuring operational duties during release windows. Automation and Infrastructure Optimization: Drive operational automation by designing and implementing automated tools and processes, ensuring resource allocation is optimized and supporting business scalability. Other Operational Practices and Work Arrangements: Providefeedback and suggestions for business architecture design and continuously produce operational technical documentation. Qualifications Bachelor's Degree or above; a degree in computer science or a related field is preferred. Experiences as Senior SRE or

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. AI Algorithms Engineer (PHD / Master Degree Only) 5 Work Days Per Week Office Near to Kaki Bukit MRT, Singapore Relocate Near Tai Seng MRT in August / September 2026 Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Job Requirements: PHD / Master Holder in Computer Science, Applied Mathematics, Electrical Engineering, Pattern Recognition, Artificial Intelligence, Automatic Control, Operations Research, Biology, Physics / Quantum Computing, Neuroscience, Statistics or a related field. Familiar with common machine learning and deep learning algorithms and keeping track with the latest SOTA implementations . Strong programming skill in Python, C / C++ , proficient in mathematical / statistical concepts and exceptional coding skills Hands-on experience with AI / ML frameworks be familiar such as Caffe, PyTorch, TensorFlow, MxNet etc. Have rich project experience in machine learning and deep learning , be familiar with common algorithm models, such as CNN, RNN, LSTM, Transformer, ViT, etc., and be able to improve and innovate models according to actual problems. Experience in familiar the design, parameter tuning and optimization methods of neural network models is a plus Experience in model compression and in the transplantation and op

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. Overview Want to build products that sit at the heart of how money moves? We’re looking for a Senior Software Engineer to help build and scale the technology powering Breeze. This is a hands-on role with real ownership. You’ll tackle complex engineering challenges, ship products customers rely on every day, and help shape technical decisions as we scale. You’ll work across the stack, partner closely with Product and Design, and have plenty of white space to improve how we build. We’re looking for an engineer who combines strong technical judgment with a product mindset. Someone who moves fast, cares deeply about quality, and gets excited about turning complex payments problems into simple, reliable experiences. If you want to build, not just maintain, and have a meaningful impact on both our product and engineering culture, we’d love to meet you. What You’ll Do Build and scale the core payment systems that power Breeze, with a focus on reliability, security, and performance Ship high-quality customer experiences using React.js and modern serverless infrastructure Own meaningful featur

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. Overview We’re hiring a Staff Software Engineer to help build and scale the technology at the heart of Breeze’s payments platform. You’ll take on some of our most complex engineering challenges, building secure, reliable systems that move money while helping shape what we build and how we build it. You’ll work across the stack, own critical systems end to end, and partner closely with Product and Design to turn complex payments problems into simple, scalable solutions. This is a hands-on Staff role with real ownership and technical influence. You’ll help set architectural direction, raise the engineering bar, guide technical decisions across the team, and build the systems and foundations Breeze needs for its next stage of growth. If you’re a strong technical builder who wants to build, not just maintain, solve hard problems, and have a meaningful impact on both our product and engineering culture, we’d love to meet you. What You’ll Do: Build and scale the systems that power Breeze, with a focus on reliability, security, and performance across our payments platform Own critical system

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including