Ai Platform Engineer in United States

About the Team DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. The Marketing Technology team is responsible for delivering best-in-class tools, data, and processes so teams at DoorDash can effectively acquire new customers, drive retention, and grow new business lines across all our audiences. Our mission is to enable teams to deliver personalized, engaging, and relevant content across all our owned and paid channels. We partner closely with Product, Engineering, Data Science, and Analytics teams to translate Marketing’s technology needs into measurable business outcomes for our Growth and Performance Marketing teams. About the Role We're looking for a Senior Associate, AI Solutions Architect to help build and scale AI-powered tools across DoorDash's Marketing teams. You'll work alongside our existing Marketing Technology AI Solutions Architects to identify opportunities where AI can solve real marketing problems, then build, test, and iterate on the solutions that make it happen. This role is grounded in hands-on building: you'll spend your time prototyping, coding, and shipping tools rather than pitching strategy from the sidelines. This is a great opportunity to grow your technical and strategic skills at the intersection of marketing and AI. You'll get mentorship from a team of builders and exposure to the full lifecycle of AI development from prototype to deployment. This role will report to the Senior Manager, Marketing Technology within the Growth Marketing organization. You're excited about this opportunity because you will… Build and deploy AI-powered tools and automations, such as automated reporting, QA frameworks, and workflow optimizations. Develop MVPs and proof-of-concepts, then iterate based on user feedback within a defined w

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! The AI Infrastructure Product Design team creates software used by engineers and researchers to prepare data, run complex workflows, and understand results. This internship offers ownership of a defined product problem from early research through a tested design and implementation handoff. Designers on this team often move between Figma and working HTML prototypes, and may hand off HTML directly to engineering. This work calls for a high standard of visual and interaction design alongside technical fluency. The role is a good fit for someone who enjoys making technically complex systems easier to understand and who uses large language models and software agents thoughtfully as part of their design and prototyping process. What you will be doing: Own a focused design project for an internal AI infrastructure product, from understanding the problem through a validated design and implementation handoff. Interview engineers and researchers, map their workflows, and turn the findings into clear product requirements, user flows, and interaction models. Create precise, implementation-ready interface designs and interactive prototypes in Figma and HTML/CSS, with careful attention to typography, hierarchy, spacing, visual consistency, interactio

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, AI Engineering, Transformation Team Overview: The Transformation Team leads strategic change initiatives to reimagine how Mastercard works and scales, simplifies, and accelerates business outcomes. The team partners across leadership, product, technology, and operations to design and implement new organizational models, embed AI across key workflows, drive enterprise-wide transformation programs, improve operating effectiveness, and ensure successful adoption of change. By combining strategy, AI engineering, organizational design, change management, and program execution, the team helps align people, processes, and priorities to support long-term growth and business performance. Role: • This job develops and executes short-term and medium-term strategic plans for AI Engineering across Mastercard, aligning functional initiatives with organizational objectives by modifying existing methods to make significant improvements to existing processes, programs, and/or policies. • Drives the development and execution of short-term functional strategies for AI/ML teams, translating organizational priorities into actionable plans and deliverables. • Collaborates with product and business leaders to translate organizational needs into scalable AI solutions and operational strategies. • Ove

At Citi Services - Global Trade and Working Capital Solutions (TWCS) Technology Organization, we are on a mission to harness the power of data to drive innovation, create exceptional customer experiences, and solve complex business challenges. Our data team is at the heart of this mission, building the scalable and resilient infrastructure that turns data into our most asset. We are a passionate, collaborative group dedicated to pushing the boundaries of what's possible. The Opportunity We are seeking an Engineering Director to join our development team. The ideal candidate is a seasoned technologist with extensive experience in building and delivering data & AI solutions for business functions. This individual will be directly and fully accountable for solution delivery and should have a history of creating strategic technology architecture roadmaps aligned with business outcomes. The successful candidate will define and execute the technology roadmap for the Data & AI portfolio of TWCS, providing strategic direction and critical input into technology decisions to ensure a scalable buildout. This role involves building strong relationships with senior business and technology partners, driving agile execution, and leading a team of expert engineers to deliver with velocity and quality. Applicants should demonstrate exceptional technical acumen, a strong data engineering background, and a proven ability to lead and provide technical direction to high-performing engineering teams. A proven expertise in Data Engineering, Data Analytics, and AI Engineering delivery at scale is essential. Responsibilities: Manage/develop multiple teams of professionals to accomplish established goals and conduct personnel duties for team (e.g. performance evaluations, hiring and disciplinary actions) as well as ensure team adheres to best practices and processes Develop vision for team aroun

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make rigorous, evidence-based talent decisions and ensures that the systems supporting those decisions are valid, reliable, fair, and accountable. About the Role As a People Data Scientist focused on AI fairness and bias testing, you will help establish how OpenAI evaluates AI-assisted People systems and high-impact talent processes. You will design and conduct rigorous assessments to identify, measure, and mitigate potential bias across the lifecycle of models, agents, decision-support tools, and automated workflows. Your work will span the entire employee life-cycle, such as hiring, performance, promotion, employee development, workforce planning, etc. You will evaluate both technical systems and the broader human-AI decision processes in which they operate, examining not only model performance but also data quality, measurement validity, differential outcomes, human oversight, and unintended consequences. We’re looking for an experienced data scientist or applied researcher who can translate complex fairness questions into defensible evaluation strategies, scalable testing infrastructure, and clear recommendations for technical teams and senior leaders. This role is preferred to be based in San Francisco, CA. In this role, you will: Define and lead fairness and bias-testing strategies for AI-assisted People processes, models, agents, and decision-support systems from development through deployment and ongoing monitoring. Design rigorous algorithmic audits and validation studies, including adverse-impact analysis, subgroup and intersectional evaluation, error-rate analysis, calibration, measurement invariance, reliability, criterion-related validity, and sensitivity testing. Identify the appropriate fairness criteria for each use case, evaluate tradeoffs among competing definitions

About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. Own the quality and impact of the team’s work across solution design, implementation, production readiness, adop

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. LEAD. STRATEGIZE. TRANSFORM. We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness. WHY THIS ROLE? This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways. WHAT YOU'LL DO: Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem. Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions. Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI. Mentor Level 3 architects on best practices for MLOps and architectural design. TECHNICAL DEPTH & RISK MANAGEMENT: Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP). Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle. Governance: Architect data security and access controls specifically for sensitive AI/ML training data. SNOWFLAKE-NATIVE TECH STACK: Snowflake Model Registry, Cortex Functions, Python,

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. The Cortex team is building the future of AI for enterprise data. This role focuses on the Search infrastructure that powers our flagship products like CoWork, Cortex Code & Cortex Agents fast, reliable, scalable and secure at the enterprise level. You will be building high-performance retrieval engines (leveraging vector search, hybrid search, and semantic indexing) that power Snowflake Cortex. This involves optimizing how billions of rows of data are indexed and retrieved in milliseconds. What you will do in this role: Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant mi

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. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Manager, Applied Field Engineering - AI/ML Product Specialists to lead a high-performing team of Applied Field Engineers within the Applied Field Engineering organization. In this hands-on leadership role, you will manage a team of Applied Field Engineers who specialize in Generative AI, Machine Learning, and Advanced Analytics. You will be responsible for coaching your team through technical sales engagements, driving execution excellence, and ensuring customers successfully activate and consume Snowflake's AI/ML capabilities. You will translate team-level insights into feedback that shapes broader strategy, working closely with your manager and cross-functional partners to align execution with organizational priorities. Responsibilities & Focus Areas: Technical Execution & Consumption Activation: Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value Coa

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Staff Product Manager, AI Foundations at Vanta, you will build the core AI capabilities that power Vanta’s AI product experiences: the agent harness our agents are built on, and the quality and evaluation stack that makes them trustworthy. The AI pillar is making Vanta the intelligence layer for security and compliance work, wherever that work starts. We build the AI products and foundations that work across Vanta: a cohesive first-party Vanta Agent experience, headless surfaces like MCP and CLI that bring Vanta into tools like Claude Code and Codex, and the shared capabilities that let every team ship high-trust AI products. This role sits behind Vanta’s customer-facing AI experiences. Today, every team shipping AI features has to answer the same hard questions on their own: how to define quality, how to evaluate it, and how to know a change is safe to ship. You will turn those answers into shared foundations, so the AI experiences our customers rely on get better and more trustworthy over time. What you’ll do as a Staff Product Manager, AI Foundations at Vanta: Own the strategy and roadmap for Vanta’s core AI capabilities: the agent harness and the AI quality and evaluation stack Live in agent traces to build intuition for how customers actually use our AI products, and turn that into the highest-leverage improvements Make Vanta’s AI products win on quality: build golden datasets, automated evaluators aligned to expert judgment, and self-serve tooling so PMs, subject-matter experts, and designers can run evals without an engineer in the loop Scale the agent harness: shape the core capabilities Vanta’s agents are built on

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. In this role you will Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles Own the development of major initiatives in the AI/ML space You'll love this job if you Are driven by impact and enjoy working on high-stakes, high-visibility projects Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members Thrive in cross-functional teams and enjoy building features alongside developers and product teams Qualifications Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field Demonstrated expertise building production-grade agentic systems and tools You are comfortable writing production quality code (we use Python) Expertise with deep learning frameworks (we use PyTorch) Familiarity in deploying machine learning models at scale in production

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role As a Senior Software Engineer on Sentry’s AI/ML team, you’ll be responsible for building the evaluation infrastructure that measures the accuracy, reliability, and real-world performance of our AI systems. This role is critical to ensuring that our debugging agents and AI-powered features behave correctly, safely, and predictably as they scale. You’ll design datasets, benchmarks, and test harnesses that turn ambiguous AI behavior into measurable signals, helping the team ship AI with confidence. In this role you will Design and build robust evaluation frameworks to measure accuracy, reliability, regressions, and edge cases in AI systems Create and curate high-quality datasets, golden test cases, and benchmarks grounded in real production data Build automated test harnesses and metrics pipelines to continuously evaluate models, prompts, and agentic workflows Partner closely with applied AI engineers and product leaders to define what “good” looks like and translate it into measurable criteria Own the evaluation lifecycle for major AI initiatives, from early experimentation through production monitoring You’ll love this job if you Care deeply about correctness, rigor, and measurement in AI systems Enjoy turning fuzzy product goals and model behavior into concrete tests and metrics Like building foundational infrastructure that unlocks faster iteration and higher confidence for the entire AI team Thrive in cross-functional environments and enjoy influencing model design through better evaluation Qualifications Minimum 5+ years of professional experience with a Bachelor’s degree in computer science, machine learni