Senior Ai Ml Architect Jobs

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Senior Product Manager for Signal Lifecycle within Trust & Safety, you'll own the product strategy for the ML platform that powers how Pinterest trains, evaluates, deploys, and measures content safety models at scale. You'll lead the development of ML Signal Management — making ML signals first-class entities with unified metadata and identity across systems. Partnering deeply with ML engineering, data science, content safety, and enforcement systems, you'll drive a platform whose scope is expanding from T&S into content quality, ads safety, and beyond. What you'll do: Own and drive the Signal Lifecycle product roadmap, including ML Flywheel infrastructure, auto-deployment, model onboarding, golden dataset management, and signal performance measurement Define and ship ML Signal Management — a unified backbone that elevates ML

The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras. This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans. In this role, you will: Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines. Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities. Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation. Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy. <li style="font-size: 11pt; font-family: Ar

What we’re doing isn’t easy, but nothing worth doing ever is. We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots. As an ML Engineer, Manipulation, you will develop and deploy learning-based manipulation systems that enable mobile robots to interact reliably with the physical world in dynamic human environments. You’ll build perception-to-action models, training datasets, evaluation tooling, and deployment pipelines that improve robustness, generalization, and safety for real-world manipulation tasks at scale. Your work will directly impact the robot’s ability to perform complex interactions consistently across real sites with minimal special-case engineering. Responsibilities Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments). Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training. Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments. Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing. Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware. Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots. Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining. Basic Qualifications Bachelor’s or Master’s degree in Robotics, Computer Scienc

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. The team plays a crucial role in the advancement of autonomous driving systems by ensuring teams have access to high-quality labeled data. This is facilitated by a comprehensive labeling stack featuring a workflow execution framework, supporting infrastructure, and a suite of data annotation tools. Nuro’s autonomy stack utilizes an industry-leading sensor suite. Our tools must handle the efficient processing and annotation of millions of points of sensor data. Our labeling infrastructure supports millions of scenes weekly. The platform team’s mission is to make labeled data accessible for all of our users. The system must be reliable and scalable. This includes everything from request submission to p

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Perception Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex computer vision or foundation models for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices. In this role, you will: Design and develop production-level, low latency, and memory-safe C++ and CUDA code for real-time perception algorithms on vehicle systems. Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks. Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment. Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries. Develop and optimize custom ML OPs and TensorRT Plugins with efficient CUDA kernels to minimize latency and maximize memory bandwidth on AI accelerators. Qualifications: Production-level C++ (14/17/20) and Python programming skills, with experience developing concurrent, memory-safe, real-time inference code for edge devices. Deep expertise in model compression technologies (e.g., model quantization such as PTQ and QAT) and mixed-precision inference frameworks (INT8, FP8, BF16/FP16). Proven experience optimizing large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs/VLAs) utilizing Efficient Attention mechanisms (

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role We're hiring a Product Design Engineer to help shape the physical form of our AI-powered devices. You'll work across the full product development cycle — concept sketches, CAD modeling, prototyping, and DFM — collaborating with electrical and ML engineers to design enclosures and mechanisms that accommodate complex sensor arrays, thermal systems, and compact compute modules. Responsibilities Lead mechanical design of core hardware (enclosures, structural components, flex assemblies, interconnects) from concept to production Convert industrial design intent into reliable, manufacturable, and precise engineering solutions, maintaining product vision and structural/functional performance Define and own specifications, tolerances, material selections, and 3D CAD across processes like injection molding, die casting, stamping, and CNC machining Drive Design for Manufacturability (DFM) and Design for Assembly (DFA) with manufacturing partners from early concept through production builds Use tolerance analysis, FEA, and DOE's to validate designs and resolve failure modes pre-assembly Collaborate with Industrial Design, Electrical Engineering, Acoustic Engineering, Reliability & Operations to unify design considerations (functionality, thermal

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. We are looking for an experienced backend software engineer to join our Road Safety & Telematics team. At Lyft, Telematics data is used to make Lyft safer by reducing the frequency and severity of accidents, which in turn also makes Lyft more affordable for riders and a better way to earn a living for drivers. The Telematics team acts as a platform team that processes petabytes of mobile sensor data — millisecond-level IMU, gyroscope, and GPS signals — through a series of DAG-based transformations and ML model inferences to detect harsh driving events and convert them into normalized risk features that other Lyft services consume. Our technology stack runs on AWS, Kubernetes, Spark, and Apache Airflow. In this role, you'll work closely with data scientists, actuarial teams, other backend and data engineers, and product management — partnering across geos to build risk-aware products that rank and reward safe drivers, help off-board unsafe ones, notify drivers in real time, and give claims agents the tools to understand exactly what happened in a ride. You'll also be a key technical partner to our insurance team as they optimize coverage costs and provider relationships. If you are a seasoned engineer with a passion for innovation, high-volume data pipelines, microservices, working in cross-disciplinary environments and possess the skills to ensure the ongoing maintenance and improvement of services, you will thrive on our team! You can read about some of the products that Telematics powers in this blog post: https://www.lyft.com/blog/posts/lyfts-impact-on-road-safety Responsibilities: Be a champion of the team's safety and affordability mission, serving as a reliable source of risk insights for teams across Lyft — from driver ranking and safety rewards to accident claims resolution and insurance

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Mach Industries is building an AI-forward autonomy stack for contested environments where GNSS and other sensing may be unavailable, degraded, or denied. As an Autonomy Software Engineer, you will design, build, and deploy the software systems that power perception, localization, navigation, planning, and mission autonomy across our product lines. This is a broad role for engineers who are deeply technical in one domain and highly effective across adjacent ones. You may come from estimation, perception, machine learning, embedded systems, or planning, but you are excited to work across the autonomy stack and deliver real capability from prototype to fielded system. Key Responsibilities Design, implement, and ship production autonomy software in modern C++ on Linux, with Python for tooling, analysis, and ML workflows. Build and integrate capabilities across perception, localization, sensor fusion, navigation, planning, and embedded inference. Take systems from prototype through simulation, software-in-the-loop, hardware-in-the-loop, flight test, and deployment. Analyze logs, simulation results, and test data to debug failures, improve robustness, and drive rapid iteration. Develop evaluation pipelines, metrics, and tooling for accuracy, lat

NVIDIA is well positioned as the 'AI Computing Company', our GPUs being the brains that power modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We are looking for a Senior AI Infrastructure Test Development Engineer to join in the mission of crafting a distributed technology for all NVIDIA teams that remotely manage 10s of 1000s of resources in a simple and controlled fashion, allowing engineers to focus on engineering and automation, rather than being burdened by manual operational tasks. The AI infra test developer engineers at NVIDIA are responsible for creating test plans, execution, and reporting, as well as developing scripts for test automation, designing and developing tools for the QA team, and developing integration tests for validation. As a test developer, you must identify weak spots and constantly design better and more creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. The ideal candidate must have strong programming skills and hands-on experience using AI development tools to improve quality and productivity across the end-to-end QA workflow. This includes leveraging AI assistants for test automation, code generation, debugging, and enhancing testing efficiency. During the interview process, we will assess your ability to effectively use AI development tools and evaluate your programming capabilities to ensure you can deliver high-quality solutions. What you’ll be doing: Architect, implement, and evolve scalable agentic end to end SWQA workflow, automated test frameworks, infrastructure, and tooling for complex software products. Define test strategy and quality gates across functional, integration, regression, reliability, and release-validation workflows. Build and maintain high-value automated coverage for Linux-

NVIDIA is well positioned as the 'AI Computing Company', our GPUs being the brains that power modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We are looking for a Senior AI Infrastructure Test Development Engineer to join in the mission of crafting a distributed technology for all NVIDIA teams that remotely manage 10s of 1000s of resources in a simple and controlled fashion, allowing engineers to focus on engineering and automation, rather than being burdened by manual operational tasks. The AI infra test developer engineers at NVIDIA are responsible for creating test plans, execution, and reporting, as well as developing scripts for test automation, designing and developing tools for the QA team, and developing integration tests for validation. As a test developer, you must identify weak spots and constantly design better and more creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. The ideal candidate must have strong programming skills and hands-on experience using AI development tools to improve quality and productivity across the end-to-end QA workflow. This includes leveraging AI assistants for test automation, code generation, debugging, and enhancing testing efficiency. During the interview process, we will assess your ability to effectively use AI development tools and evaluate your programming capabilities to ensure you can deliver high-quality solutions. What you’ll be doing: Architect, implement, and evolve scalable agentic end to end SWQA workflow, automated test frameworks, infrastructure, and tooling for complex software products. Define test strategy and quality gates across functional, integration, regression, reliability, and release-validation workflows. Build and maintain high-value automated coverage for Linux-based, containeriz

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. About our Team: Micron’s AI Automation and Data Engineering team drives enterprise data strategy and innovation by delivering scalable data platforms that power advanced analytics, artificial intelligence, and business automation. The team partners across engineering, operations, and business functions to modernize data ecosystems and enable data-driven decision making. Position Overview: Micron is seeking a Senior AI Automation Data Engineer to design, build, and scale modern enterprise data platforms that support AI, automation, analytics, and digital transformation initiatives. This role will focus on cloud-based data solutions, enterprise data modernization, and the development of secure, governed, and AI-ready data products! Responsibilities: Design, develop, and maintain scalable data pipelines and integration frameworks for structured and unstructured data. Build and optimize cloud-based data solutions using Snowflake and AWS and/or GCP technologies. Lead modernization efforts by migrating legacy data platforms and implementing ETL/ELT architectures. Develop AI-ready datasets and data products that enable analytics, machine learning, generative AI, and automation initiatives. Establish data governance, security, monitoring, and CI/CD standard processes to ensure reliable and compliant data platforms. Minimum Qualifications: Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technica

Job Details: Job Description: Why Join Us Join a team shaping the future of AI on Intel platforms. You will work on cutting-edge technologies that accelerate Large Language Models, Generative AI, and other advanced AI workloads on next-generation Intel GPUs. This role offers the opportunity to collaborate with experts across hardware architecture, compilers, runtime systems, and AI frameworks while developing skills that span the full AI software stack. Your work will have direct impact on delivering industry-leading AI performance and enabling the next generation of AI applications. Intel is seeking a Senior AI Systems Software Engineer to drive optimization strategy and technical leadership across the AI software stack. In this role, you will lead the development of high-performance software solutions that accelerate AI inference workloads, including Large Language Models (LLMs), Generative AI, and emerging machine learning applications on Intel GPU platforms. You will work across software, compilers, runtimes, frameworks, and hardware architecture teams to deliver breakthrough AI performance and influence future product direction. What You’ll Do Key responsibilities will include but not limited to: Lead optimization initiatives for AI inference workloads on Intel GPUs. Define and drive performance optimization strategies across compilers, runtimes, and GPU kernels. Architect software solutions that improve scalability, efficiency, and performance. Profile, benchmark, and analyze complex AI workloads to identify system bottlenecks. Influence hardware and software co-design decisions through performance characterization and workload analysis. Drive cross-functional technical initiatives spanning architecture, compiler, framework, and r

We are hiring a Senior AI Engineer to build and operate production AI systems and infrastructure. In this role, you will work on AI agents, MCP servers, agent evaluation, and Temporal-based workflow frameworks. This is a hands-on engineering role for someone who can move between backend systems, AI application development, deployment, and production support. You will help build reliable services and frameworks that make AI agents usable, measurable, and dependable in production. What you’ll be doing: Build and deploy AI agents that use tools, call services, manage context, and execute multi-step tasks. Develop and maintain MCP servers and tool integrations used by internal AI systems. Build workflow infrastructure using Temporal or similar orchestration frameworks. Design and implement agent evaluation flows, test suites, quality metrics, and feedback loops. Design backend services, APIs, persistence layers, and platform components for AI applications. Work with SQL and NoSQL databases, queues, distributed systems, and cloud-native infrastructure. Build CI/CD pipelines, Docker images, Kubernetes deployments, monitoring, and operational tooling. Debug production issues across services, workflows, agents, tools, models, and infrastructure. Collaborate with engineering, product, infrastructure, and data science teams to turn requirements into reliable systems. What we need to see: 5&#43; years of experience and a practical understanding of how AI agents are built, including tool use, state, context, and multi-step execution. Bachelors degree or equivalent experience. Experience with at least one open-source agent or LLM application framework, such as LangChain/LangGraph. Strong software engineering background, especially in backend development. Experience with distributed systems, workflow orchestration, and prod

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! NVIDIA Architecture Modeling group is looking for Architects, Software Engineers, and AI application developers to join our various architecture efforts across GPU's and SOC's. In this position, you will be working with other world-class architects on enabling state-of-the-art GenAI applications integrated with simulation platform and architecture teams' process workflows. What you’ll be doing: Develop and deploy scalable GenAI applications that integrate with existing workflows and enhance overall productivity Use state-of-the-art AI tools and techniques to accelerate GPU/ SOC Architecture modeling Work with hardware architects to identify how to best design, customize, and deploy AI-based solutions to their specific problem domains. Collaborate with infrastructure engineers to improve existing automated workflows by incorporating LLMs and establishing best practices for future solutions. Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge. What we need to see: BS, MS, PhD or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a relate

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role WRITER is looking for a customer success professional who will own deployment and activation success across a customer portfolio. You'll embed deeply into your customers' organizations, understand their business objectives, and build the programs, communities, and frameworks that turn AI investment into measurable outcomes. You'll partner closely with a Transformation lead to identify the right WRITER capabilities for each use case, then design and execute the strategies that drive meaningful adoption: building champion networks, running customized workshops, and advising customers on how to scale their AI programs over time. The ideal candidate brings a builder's mindset to customer success: you're not waiting for customers to engage, you're creating the conditions for it. This is a hybrid role based in our San Francisco or Seattle hub. 🦸🏻‍♀️ What you'll do Own activation and platform success Deeply understand each customer's specific use cases, business obj