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At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Deal Reporting team is responsible for building our critical capital partner integrations, as well as services to automate funding processes safely and reliably. We partner with Product and Capitals Markets teams to understand and implement complex financial structures, integrations and reporting. We are looking for a highly motivated Staff Software Engineer to help empower Deal Reporting's first international team, and build integrations, services, and testing infrastructure to power the funding of every Affirm loan. What You'll Do: · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. · You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by providing feedback and guidance, and leading by example. · “On-Call Rotation - There would be an on-call rotation for this role as a requirement”. What We Look For: · You have 7+ years of experience designing, developing and launching backend systems a

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Deal Reporting team is responsible for building our critical capital partner integrations, as well as services to automate funding processes safely and reliably. We partner with Product and Capitals Markets teams to understand and implement complex financial structures, integrations and reporting. We are looking for a highly motivated Staff Software Engineer to help empower Deal Reporting's first international team, and build integrations, services, and testing infrastructure to power the funding of every Affirm loan. What You'll Do: · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. · You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. · You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For: · You have 7+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. · You have an extensive track record of dev

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 want to work on commercializing autonomy and robotics in a service used by millions of people — and on bringing the merchant partners who power that service along with us — then we want to talk to you! About the Role Come help us redefine last-mile logistics through robotics, automation, and other advanced technologies. Autonomy only works when merchants — restaurants, retailers, and other partners — can reliably interact with our robots: handing off orders, troubleshooting edge cases, and trusting the experience enough to keep using it. This role owns that side of the equation. We're looking for a Merchant Success & Growth lead to build the strategy and operational mechanisms that get merchants onboard, keep them performing, and turn their day-to-day reality into a tight feedback loop for product and engineering. You're excited about this opportunity because you will… Own merchant adoption and performance KPIs for autonomy end-to-end — defining what "successful merchant interaction with a robot" means, instrumenting it, and driving improvement against it. Build the playbooks and operational mechanisms to onboard merchants to autonomy — from first conversation through training, go-live, and steady-state ops — and scale them across markets. Partner with sales, account management, and field ops to recruit and ramp the right merchant cohorts for each stage of the product, and design experiments that test new merchant-facing features and handoff models. Define merchant performance benchmarks (handoff success rate, dwell time, dasher/robot interaction quality, merchant CSAT) and run the cadence that holds partners and internal teams accountable to them. Stand up the feedback loop from the field back to product and engineering — turning merchant complaints, edge cases, and frontline observations into prioriti

About the Team As one of DoorDash's core operations teams, Customer Experience and Support Operations, ensures that when there are bumps in the last mile, there's always someone there to help make things right. Our team designs and manages DoorDash's large and growing global network of support centers to create the best customer experiences, with the ultimate goal of delivering an outstanding customer experience as reliably as possible. About the Role We are looking for Merchant Experience Partners to partner with our highest-value merchants to help solve their most pressing issues and provide the opportunity to improve their overall merchant experience as we continue to increase our last-mile logistics platform. As a Merchant Experience Partner, you will play a crucial role within the Merchant Experience team by providing our merchants with a direct contact for all of their support needs and focusing your efforts on ensuring overall Merchant success on the DoorDash platform. You will build long-lasting relationships with our Merchants through excellent customer service and strategic problem-solving. Not only will you partner with our Merchants, but you will work with Account Owners and own a book of business as their support contact. You will be a part of a program to shape support as a differentiator in the marketplace through high-quality, white-glove service. You're excited about this opportunity because you will… Collaborate and troubleshoot important issues for Merchants via phone and web Build relationships with Merchant partners by being the main contact and expert for a portfolio of Merchants spanning Enterprise and small - medium businesses Promote retention and overall Merchant success through white-glove service Perform daily phone outreach to proactively resolve issues for Merchants Prioritise and escalate issues in partnership with our teams Managing conflicting deadlines, ensuring cross-functional collaboration Have a solutions-focussed mi

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team works to ensure that increasingly capable models behave safely and reliably in real-world environments. We investigate emerging model failures, define the behavior models should exhibit instead, and develop the data, evaluations, monitoring, and safeguards needed to improve and validate that behavior. Our work connects alignment research with the practical challenges of training and deploying frontier models. About the Role In this role, you will shape how OpenAI understands and addresses real-world risks that emerge from model misalignment as models become more autonomous and operate over longer horizons. You will investigate how misaligned behavior emerges across extended trajectories - including when models persist toward the wrong objective, take unsafe shortcuts, lose track of instructions, exploit weaknesses in their environment, or circumvent constraints - and translate these insights into behavioral policies, evaluations, monitoring, and safeguards. This role is ideal for someone who wants to turn alignment and safety concerns into concrete, empirically grounded improvements to frontier AI systems. Your Responsibilities: Identify vulnerabilities that emerge as models interact with tools, data, and external systems, and translate them into model- and system-level safeguards. Develop threat models and empirical frameworks for understanding harmful outcomes from misaligned behavior. Build frameworks for understanding harmful outcomes arising from model misalignment. Identify the underlying behaviors and system conditions that drive those outcomes. Turn findings into policy frameworks, evaluation criteria, online measurement and safeguards. Develop human data campaigns and gold sets to ground measurement and evaluation of eme

Location Details: India, Remote At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join Our Team... Here at GoDaddy, the ML Engineering (MLE) team exists as the backbone of our machine learning infrastructure, enabling ML scientists and product teams across Domains to ship models to production reliably, efficiently, and at scale. This team owns the full lifecycle of ML systems — from CI/CD pipelines and model serving infrastructure to GPU workload orchestration and observability. Through disciplined engineering practices, thoughtful system design, and close collaboration with ML scientists, data engineers, and product teams, we deliver the platform that powers domain search, pricing, recommendations, and emerging AI experiences for millions of customers worldwide. We are currently looking for an experienced, highly motivated Senior Engineering Manager to lead our ML Engineering team based in India. This is an established team with existing engineers — we expect the candidate to ramp up quickly on our ML infrastructure stack, build strong relationships with the team, and partner with both India-based teams and US-based teams to drive execution and grow the team further. This individual will join us on our journey to build and scale ML infrastructure that serves real-time predictions at low latency, automates model deployment and promotion, and provides the observability and reliability guarantees that production ML systems demand. Become part of a team that bridges the gap between ML research and production engineering — shipping systems that directly impact GoDaddy's core revenue. What you'll get to do... Lead a team o

About the Role We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

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 The Storage Abstractions (STAX) team builds the software layer through which Stripe services access stored data. We own the database SDKs that hundreds of Ruby and Java services use to read and write data safely, reliably, and efficiently without needing to understand the underlying database, routing, or operational complexity. Our work creates leverage across Stripe: by providing stable interfaces and safeguards at the storage layer, we help teams build products with confidence while enabling Stripe’s data architecture to evolve. Alongside engineers, we are designing for AI agents as customers of this foundation, making storage capabilities discoverable, interoperable, and safe to use across languages and storage backends. What you’ll do As a Staff Software Engineer on STAX, you will set technical direction and lead multi-year initiatives at the intersection of developer infrastructure, data access, and AI. You will work hands-on with engineers across Stripe to make storage access simpler, safer, and more interoperable, while helping product and infrastructure teams evolve their systems without fleet-wide migrations. You will help turn Stripe’s AI strategy into practical developer infrastructure by treating AI agents as customers of the storage layer. This is an opportunity to build frameworks and interfaces that make complex storage operations discoverable, interoperable, and safe for both human developers and agentic workflows, while rais

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and

We're looking for a Principal Software Engineer to join our CSP Engagements team as the technical focal point for rack-scale system SW/FW, working with CSP engineering teams to ensure they can deploy, monitor, and operate these systems reliably at fleet scale. In this role, you will collaborate with NVIDIA's cross-functional rack-scale system SW/FW engineering teams with dedicated CSP-facing technical leadership. Your focus is on the system-level software that manages, monitors, and recovers the rack as a whole — fabric management, GPU/NVSwitch error handling and recovery, health telemetry APIs, firmware update orchestration, and SW-driven serviceability. You will drive work streams with CSP engineering teams to build shared understanding of the architecture, incorporate their operational feedback, and ensure integration readiness. What you'll be doing: Drive rack-scale SW/FW architecture alignment across CSP engagements — including fabric management software, link health monitoring, GPU/NVSwitch error handling, SW/FW serviceability features (e.g., hot-plug support, component isolation, firmware-driven recovery), and multi-component firmware orchestration Drive technical work streams with CSP engineering teams on rack-scale system software — ensuring they deeply understand fabric management, NVSwitch behavior, error handling and recovery policies, health telemetry APIs, and SW/FW-controlled recovery operation Capture and synthesize CSP engineering feedback on rack-scale system software — health monitoring APIs, SW-driven serviceability workflows, firmware update orchestration, and error recovery behavior — champion that feedback into NVIDIA's architecture decisions Collaborate with multi-functional teams to ensure customer operational requirements are reflected in system software and firmware development Identify cross-CSP patterns in rack-scale SW/FW iss

Senior Manager, Logistics Security Description - At HP, we create technology that helps people and businesses bring their ideas to life. Our global supply chain plays a vital role in that mission, moving high-value products safely and reliably to customers around the world. We are looking for a collaborative and solutions-oriented Senior Manager, Logistics Security to help protect our logistics network, strengthen transportation risk programs, and lead efforts that reduce loss, improve carrier performance, and support a secure customer experience. Core responsibilities Own logistics security strategy for HP's transportation network. Manage loss, theft, damage, shortage and mis-delivery incidents across carriers, warehouses and distribution partners. Lead transportation claims management, including investigation, documentation, recovery and settlement. Manage relationships with major LSPs, carriers, freight forwarders and 3PLs. Investigate high-value shipment incidents and identify root causes. Develop controls to prevent cargo theft, fraud, unauthorized access and product diversion. Establish security standards for transportation lanes, warehouses and high-risk locations. Track claims and losses using KPIs such as: Claim $ / shipment Loss rate Damage rate Theft incidents Recovery % Claim cycle time Carrier performance Partner with Supply Chain, Logistics, Finance, Legal, Compliance, Security and Insurance teams. Lead corrective/preventive actions with logistics service providers. Review carrier contracts and ensure appropriate liability and insurance coverage. Establish escalation processes for major incidents. Conduct risk assessments of logistics providers and distribution locations. Use dat

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company. The Difference You Will Make: The Service Tools team's mission is to enable Airbnb backend developers to develop, test, and maintain their code quickly and reliably. We own the standard development lifecycle for service owners — from AI-assisted development, through the build system, integration testing and code review, to how services get built for deployment. This represents Airbnb's largest cohort of developers, and you will ultimately be responsible for their productivity. As a Staff Engineer, you will set technical direction rather than only deliver against it. You will own a platform-spanning area of the developer lifecycle end to end — framing the problem, building the measurement that proves it matters, driving a roadmap with partner teams across the company, and growing the engineers who build it with you. The next 18–24 months of this platform are genuinely open: agentic development is changing what the inner loop looks like, and we want someone who wants to help decide what it should become. A Typical Day: Owning a multi-quarter, platform-spanning workstream — agentic developer workflows, intelligent build infrastructure, test excellence, codebase modernization, or developer observability — as the DRI other teams come to Advancing our AI-assisted developme