Production Engineer in Singapore

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.

Manufacturing Equipment/Production Engineer — Fab 10N/X, Singapore. Apply via Workday.

Manufacturing Equipment/Production Engineer — Fab 10N/X, Singapore. Apply via Workday.

Manufacturing Equipment/Production Engineer — Fab 10N/X, Singapore. Apply via Workday.

Manufacturing Equipment/Production Engineer — Fab 10N/X, Singapore. Apply via Workday.

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

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Must be a permanent resident or citizen of Singapore. Responsibilities Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. Product Feedback Loop: D

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 Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. We work closely with hardware design teams, manufacturing partners, suppliers, and data center operations to deliver the compute platforms that power frontier AI. The Manufacturing Engineering team ensures our hardware can be built, tested, deployed, and supported at hyperscale. We bridge Hardware Engineering, Quality, Supply Chain, Contract Manufacturers, and Hardware Operations to continuously improve manufacturing performance throughout the product lifecycle. As our fleet grows globally, sustaining manufacturing engineering becomes increasingly important to maintain product quality, improve manufacturability, and rapidly resolve production issues. About the Role We are seeking a PCBA Manufacturing Engineer (Sustaining) to support production and continuous improvement of printed circuit board assemblies (PCBAs) used throughout Industrial Compute hardware platforms. This role focuses on sustaining engineering after product launch. You'll partner closely with Hardware Design, Quality, Manufacturing, Test Engineering, Supply Chain, and our contract manufacturers to resolve production issues, improve manufacturing yield, reduce failures, implement engineering changes, and ensure stable high-volume manufacturing. The ideal candidate has experience supporting complex server, networking, accelerator, storage, or high-performance electronics manufacturing environments. Key Responsibilities Own sustaining manufacturing engineering for PCBA production across multiple hardware platforms. Drive root cause investigations for manufacturing defects, field failures, and production escapes. Partner with Hardware Design Engineers to improve manufacturability (DFM/DFA/DFT). Support engineering change orders (ECOs) and manufacturing change implementation. Work directly with contract manufacturers to improve production yield, cycle time, and quality. Analyze manuf

About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking a Manufacturing Test Engineer to own and drive manufacturing test strategy, development, and execution for complex AI hardware systems. This role will define and implement test coverage across the product lifecycle, including ICT, functional circuit test, tray-level functional test, and system manufacturing test. You will work closely with hardware design engineering, diagnostic/software teams, manufacturing engineering, quality, and external system integrators and suppliers to translate product requirements into robust, scalable, and production-ready test solutions. You will also play a key role in reviewing test data, debugging failures, improving yield, and ensuring manufacturing test readiness from early development through volume production. In This Role, You Will: Define and drive the manufacturing test strategy for boards, trays, and system-level hardware assemblies across EVT, DVT, PVT, and production ramp. Develop and manage test coverage for: ICT / structural test FCT / board-level functional test Tray-level functional and integration test System-level manufacturing and bring-up test Partner closely with electrical engineering, system engineering, and diagnostic/software teams to define test requirements, review manufacturing test scripts and diagnostics, validate failure isolation needs, debug hooks, logging, and production screening strategies. Translate engineering requirements into practical, scalable manufacturing test plans that

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing engineer, who will be responsible for driving technical initiatives related to manufacturing to ensure product success from concept to launch and through mass production with a specific focus on PCB and PCBa manufacturing and process. You’ll have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams,TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. This role is based in San Francisco, CA. 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: In this role, you’ll be responsible for driving manufacturing and quality initiatives to ensure product success from concept to launch Lead the product design and the manufacturing process for next-gen AI hardware system development, you will have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams, TPMs and external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. Lead the team to establish NPI product manufacturing process, systems and quality controls, defining clear milestones and deliverables, drive internal process improvements across multiple terms and functions Provide hands-on product manufacturing analysis during desi

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

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About North: North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. Why this role? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-thei