Technical Program Manager, Agentic Development Platform (Modeling & Evals)

Logos Space is at the forefront of revolutionizing satellite communications with our Low Earth Orbit (LEO) satellite system, designed to meet the connectivity demands of commercial enterprises and government entities. We aim to bridge a crucial gap in the market by delivering robust, high-performance satellite-based connectivity solutions for our clientele around the globe. Our business customers will benefit from contracts that specify performance standards for broadband, which we will integrate into our system from the outset. Speed and reliability are the cornerstones of our infrastructure, ensuring seamless cloud and data center connectivity to fixed, maritime, and aerial terminals worldwide.Led by a team of seasoned engineers with extensive experience in networking and satellite technology, Logos Space is committed to innovation and excellence.Position Overview & ResponsibilitiesAs a member of the Networking team at Logos Space, you will play a pivotal role in ensuring the success of our network through the development of software-defined networking, performance monitoring, and other vital components of the ground segment. Your collaboration with other spacecraft design aspects—such as RF, power management, and more—will be essential. This network will uniquely provide services at Layer 2, 2.5, and 3, necessitating the development of methodologies to manage flows with enterprise-level assurance. Your work will evolve from conceptual frameworks to discrete event simulations at the message level, ultimately culminating in a digital twin of the deployed system.As an Algorithm and Network Simulation Engineer, you will be instrumental in designing, optimizing, and validating our pioneering hybrid space and terrestrial network. Your responsibilities will include creating intricate simulation models and algorithms to analyze performance metrics, assess emerging technologies, and enhance network behaviors within this complex ecosystem. This is a remarkable opportunity to spearhead core innovations within our network architecture.We're seeking engineers who thrive in dynamic environments and relish the challenge of transforming abstract design concepts into tangible hardware ready for testing and deployment. If you have a passion for solving complex problems, we want to hear from you!

Role Overview Anduril Industries is hiring a Staff System Modeling Engineer for Warfighter Systems in Mountain View, California. This role centers on applying advanced modeling methods to improve military systems and support mission success. Work here shapes the effectiveness of defense solutions and has a direct impact on operational outcomes.

Reliable Robotics builds automated aviation systems aimed at making air transportation safer and more efficient. The team includes engineers from aerospace, robotics, and autonomous vehicle backgrounds, all working to advance aviation technology. Role overview The Senior Model-Based Systems Architect will design and develop the company’s internal digital engineering ecosystem. This role involves more than configuring existing tools: the architect will define the formal information schema that connects systems, software, and certification data throughout the organization. What you will do Design and implement a digital engineering framework to support automated aviation systems Create and maintain a unified information schema linking systems, software, and certification data Collaborate with engineering teams and internal tool developers to ensure integration and smooth data flow Establish a scalable, consistent single source of truth for engineering information Location This position is based in Mountain View, CA.

About Contextual AIAt Contextual AI, we are at the forefront of transforming how AI agents operate by addressing one of the most significant challenges in the field: context. By providing the right context at the right moment, we enable enterprises to achieve the accuracy and scalability required for effective AI deployment. Our innovative enterprise AI development platform bridges cutting-edge AI research with the practical needs of developers, allowing them to seamlessly ingest, query, and integrate data from various enterprise sources into their workflows.Founded by the pioneers of Retrieval-Augmented Generation (RAG), our technology forms the backbone of the context layer that connects foundational AI models with relevant real-time information. Supported by visionary venture capital, we are not merely participating in the enterprise AI revolution; we are leading it. Join us as we create a future in which AI not only answers queries but also revolutionizes business operations.About the RoleAs a Member of Technical Staff focused on LLM Systems & Performance, you will join a dedicated and impactful team responsible for building and optimizing LLM systems from end-to-end. Your work will range from developing Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) pipelines to creating high-throughput inference clusters for production environments. You will collaborate with both researchers and engineers to design advanced models and the supporting infrastructure for our context layer.What You'll DoEnhance and optimize components of our SFT and RL training pipelines (e.g., Verl, SkyRL), focusing on areas such as data loading, training loops, logging, and evaluation.Contribute to the development of LLM inference infrastructure (e.g., vLLM, SGLang), including optimizations for batching, KV-cache management, scheduling, and serving.Utilize profiling tools like Nsight to analyze and improve end-to-end performance metrics (throughput, latency, compute/memory/bandwidth) by identifying and resolving bottlenecks.Engage with distributed training and inference systems using technologies such as NCCL, NVLink, and various parallelism strategies on multi-GPU clusters.Assist in experimenting with and implementing quantization techniques (e.g., INT8, FP8, FP4, mixed-precision) for both training and inference.Write and optimize GPU kernels utilizing CUDA or Triton, employing techniques such as FlashAttention and Tensor Cores as appropriate.Collaborate with researchers to advance ideas from concept to prototype, through scaled experiments, and into production.

Waymo is at the forefront of autonomous driving technology, striving to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been dedicated to developing the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access while aiming to reduce the tragic loss of lives due to traffic accidents. The Waymo Driver not only fuels our fully autonomous ride-hailing service but is also adaptable across various vehicle platforms and applications. With over ten million trips solely for riders and extensive experience from autonomously navigating over 100 million miles on public roads, alongside tens of billions of miles in simulation across more than 15 U.S. states, we are leading the charge in this transformative technology.The Large Model Evaluation team plays a pivotal role in advancing Waymo's AI vision. As we integrate cutting-edge Large Language Models (LLMs) and Vision-Language Models (VLMs), our aim is to construct sophisticated AI systems capable of addressing the multifaceted challenges of real-world driving. Central to our achievements is the ability to accurately measure our progress. In a landscape where robust evaluation serves as a critical barrier to deploying large models, the intricacies of this task at Waymo are particularly complex and safety-sensitive. We seek quantitatively driven engineers to innovate and propose novel methodologies for evaluating the ML models utilized in the Waymo Driver.

Applied Intuition, Inc. creates digital infrastructure and tools that support physical AI across industries such as automotive, defense, trucking, construction, mining, and agriculture. The company is headquartered in Sunnyvale, California, and operates offices in cities including Washington, D.C., San Diego, Ft. Walton Beach, Ann Arbor, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo. Eighteen of the world’s top twenty automakers, as well as the U.S. military and allied forces, rely on Applied Intuition’s technology. For more details, visit applied.co. The team values an in-office culture, with most employees onsite five days a week. There is flexibility for occasional remote work, starting the day from home, or adjusting hours for family commitments. Role overview This Software Engineer - Performance Optimization role is based in Mountain View, California. The focus is on optimizing application-layer software for embedded systems used in autonomous driving technology. What you will do Work across several components of the autonomous driving software stack Develop new features and drive performance improvements for embedded systems Requirements Experience optimizing application-layer software for embedded systems

Waymo is a pioneering force in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo focuses on developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and significantly reduce traffic-related fatalities. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips completed and extensive experience from driving more than 100 million miles on public roads, complemented by simulations totaling tens of billions of miles across over 15 U.S. states, we are at the forefront of our industry.The Large Model Evaluation team plays a crucial role in advancing Waymo's AI ambition. As we leverage advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs), our goal is to create cutting-edge AI systems that navigate the complexities of real-world driving scenarios. Our progress hinges on our ability to measure performance effectively. With robust evaluation being essential for deploying large models, the challenges we face are particularly intricate and safety-critical. We are seeking engineers with a quantitative mindset to explore and establish innovative methods for assessing the machine learning models utilized in the Waymo Driver.

Join Nuro as a Senior Software Engineer, where you will play a pivotal role in enhancing our performance tooling and infrastructure. You will work on cutting-edge technologies to optimize our systems for efficiency, scalability, and performance. If you are passionate about building robust software solutions and driving innovation, we want to hear from you.

About UsAt MAI (pronounced “my”), we are committed to making advanced advertising technology accessible to all. Our vision is to provide powerful marketing tools that were once limited to large corporations with vast budgets. We harness the power of AI agents to automate and enhance performance marketing, enabling small and mid-sized businesses to maximize their advertising spend efficiently without relying on agencies or spending countless hours managing campaigns manually.Founded by industry experts from Google and Instacart, we have successfully completed a $25 million Seed funding round led by Kleiner Perkins, aimed at accelerating our growth. This investment will help us expand our teams and bring our concept of intelligent, autonomous marketing to fruition. Our AI agents have demonstrated their effectiveness, helping clients achieve 40% more sales while managing millions in monthly Google Ads expenditure. We are experiencing a surge in client interest and our waitlist continues to grow.Why Join Us Now?The journey of constructing marketing strategies for intelligent AI agents is a groundbreaking endeavor, and at MAI, you can help us define this new frontier. As a Performance Marketing Specialist, you will play a vital role in our marketing team, influencing how we connect with and scale our engagement with eCommerce brands.Your ResponsibilitiesTransform client marketing goals into actionable media plans, ensuring prompt and high-quality execution across various advertising platforms.Oversee comprehensive campaign operations across platforms like Google Ads and Meta Ads, partnering with AI agents to optimize performance, experiment with strategies, and deliver regular performance insights.Implement marketing initiatives such as seasonal campaigns, brand promotions, budget reallocation, and adjustments to ROI targets.Supervise account health and AI agent activities to mitigate performance issues, sustain operational stability, and ensure the ongoing effectiveness of campaigns.Your QualificationsRequired:Bachelor’s degree in Marketing, Business, Data Analytics, or a related discipline.3–6 years of practical experience in digital marketing operations or campaign management.Demonstrated success in managing full-funnel campaigns across key channels (Google, Meta, etc.) focusing on brand awareness, consideration, engagement, and conversion.

Reliable Robotics develops automated aviation systems to improve safety and accessibility in air transportation. The team includes engineers from aerospace, robotics, and autonomous vehicle backgrounds, all working to advance aviation technology and make air travel more dependable. Role overview The Senior Guidance, Navigation, and Control (GNC) Modeling Engineer focuses on creating and improving physics-based models that underpin both rapid design changes and certification-level validation of GNC software. This role plays a key part in ensuring the accuracy and reliability of automated flight systems. What you will do Develop and refine physics-based models to support GNC software Run simulation analyses to test and validate GNC algorithms Compare simulation outputs with real-world data to verify model accuracy Contribute to iterative design and certification processes with high-fidelity modeling Location This position is located in Mountain View, CA.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Established in 2009 as the Google Self-Driving Car Project, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and saving countless lives from traffic-related accidents. Our technology empowers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and product applications. With over ten million rider-only trips facilitated by the Waymo Driver and more than 100 million miles driven autonomously on public roads, we are paving the way for safer transportation.The Perception team is responsible for developing systems that interpret the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles. Our collaborative efforts with downstream teams focus on optimizing and integrating these systems within the Waymo Driver. We engage in innovative research to tackle real-world challenges and work closely with research teams at Alphabet. Our engineers have access to extensive driving data from diverse sensors, allowing us to (1) create efficient learning methods from vast real-world datasets, (2) build and train models at scale, (3) analyze real-world behaviors, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

Waymo, an innovator in autonomous driving technology, is dedicated to becoming the world's most reliable driver. Originating as the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver supports our fully autonomous ride-hail service and can be integrated into various vehicle platforms for diverse applications. With over ten million rides provided and experience from driving more than 100 million miles on public roads combined with billions of miles in simulation across 15+ U.S. states, we’re at the forefront of a transportation revolution.The Perception team is responsible for developing systems that learn spatial-temporal representations and their semantic meanings within the autonomous vehicle's environment. Collaborating closely with other teams for optimization and integration into the Waymo Driver, we engage in research to tackle practical challenges and work with Alphabet's research teams. With access to millions of miles of diverse driving data, our engineers can (1) create methods for efficient and continuous learning from large-scale real-world data, (2) build and train models at scale, (3) analyze real-world behavior to manage complex interactions, and (4) optimize models for our onboard and offboard hardware.In this hybrid role, you will report directly to a Technical Lead Manager.

Waymo is at the forefront of autonomous driving technology, committed to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, we have dedicated ourselves to developing the Waymo Driver—The World’s Most Experienced Driver™. Our mission is to enhance mobility access while significantly reducing traffic-related fatalities. With over ten million rider-only trips powered by the Waymo Driver, we have accumulated extensive experience, having driven more than 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.The Waymo AI Foundations team is dedicated to creating machine learning solutions that tackle complex challenges in autonomous driving. Our goal is to ensure the safe operation of Waymo vehicles in various cities and under diverse driving conditions. We actively collaborate with other research teams within Alphabet, focusing on areas such as reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.This position follows a hybrid work schedule and reports directly to a Staff Research Scientist / Tech Lead Manager.

Intrinsic Robotics, part of Google's AI robotics division, is dedicated to advancing industrial robotics by combining artificial intelligence, perception, and simulation. The team’s mission is to make intelligent robotics more accessible and practical for businesses, entrepreneurs, and developers. Interns at Intrinsic Robotics work alongside engineers, roboticists, designers, and technologists in a collaborative environment. Projects here directly influence real-world robotics applications and contribute to new economic opportunities in the field. Role overview The Vision Foundation Model Research Intern will focus on designing, training, and evaluating vision foundation models for industrial robotics. Responsibilities include deploying these solutions with industry partners and aiming for high model performance in real-world scenarios. What you will do Contribute to robotics software development, including projects on the Flowstate platform. Work closely with experienced professionals and follow modern software development practices. Research and implement deep learning models in Python, using PyTorch or Jax. See the results of your work applied with customers in the industrial robotics sector. Requirements Current enrollment in a Master's program in Computer Science or a related discipline (PhD candidates are preferred). Strong programming skills in Python and practical experience with PyTorch or Jax. Knowledge of training foundation models across multiple nodes. Interest or background in end-to-end robotics applications or integrating robotic hardware in industrial settings. Ability to troubleshoot, launch, and debug training and inference workflows. Clear verbal and written communication abilities. Location This internship takes place in Mountain View, California.

Waymo is at the forefront of autonomous driving technology, striving to become the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to advancing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility and save lives that are often lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hail service but is also adaptable across various vehicle platforms and use cases. With over ten million rider-only trips completed, our technology has driven autonomously for more than 100 million miles on public roads, supported by tens of billions of miles in simulation across 15+ U.S. states.Our Compute Team plays a pivotal role in delivering the compute platform that runs the software stack of fully autonomous vehicles. We specialize in designing high-performance custom silicon, developing cutting-edge system-level compute architectures that maximize performance, power efficiency, and minimize latency. Our multidisciplinary team thrives on collaboration, working closely with various engineering teams to ensure both hardware and software are optimized for peak performance. We are looking for passionate and talented individuals to join us in developing one of the highest-performing automotive compute platforms in the world.In this hybrid role, you will report to a Hardware Engineering Manager.

Waymo, the leader in autonomous driving technology, aims to be the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo is dedicated to developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access and significantly reduce traffic-related fatalities. With over ten million rider-only trips facilitated by our technology, which has autonomously navigated more than 100 million miles on public roads and countless simulations across more than 15 U.S. states, we are at the forefront of autonomous transportation.The Waymo Applied Research team is devoted to crafting machine learning solutions that tackle key challenges in autonomous driving, focusing on safely operating Waymo vehicles across diverse cities and under varying driving conditions. We thrive on collaboration, fostering partnerships with other research teams within Alphabet to push the boundaries of innovation.In this hybrid role, you will report to a Technical Lead Manager.

About CreatifyCreatify is pioneering the first comprehensive AI-driven advertising platform that automates the entire video ad lifecycle—from scripting and virtual avatar generation to testing, optimization, and distribution across major platforms like Meta, TikTok, and YouTube.In just 18 months, we have achieved over $10 million in annual recurring revenue (ARR), catering to more than 1.5 million users across over 10,000 teams. Renowned brands such as Alibaba, HubSpot, Binance, NewsBreak, and Zumper leverage Creatify to generate tailored, high-performance video advertisements in mere minutes.We have secured $24 million in funding from top Silicon Valley investors, including WndrCo, Kindred Ventures, Millennium New Horizons, NFDG, Comcast Ventures, Creator Ventures, and Leadout Capital. Explore our recent features in Fast Company, TechCrunch, Bloomberg TV, and our acknowledgment as one of the IVP Enterprise AI 55 in 2024.Located in Mountain View, our team consists of dedicated AI researchers, engineers, and advertising professionals. Be a part of our mission to revolutionize the advertising landscape through AI innovation.

Waymo LLC develops autonomous driving technology, building on its origins as the Google Self-Driving Car Project. The Waymo Driver, at the core of its ride-hailing service, has completed over ten million rides and driven more than 100 million miles on public roads, plus tens of billions of miles in simulation across 15+ U.S. states. The Hardware Engineering team brings together electrical, mechanical, reliability, software, and vehicle engineers. This group designs and integrates the sensors and systems that enable Waymo's autonomous vehicles. The team values curiosity, technical skill, and collaboration. This LiDAR Performance Validation Hardware Engineer role is based in Mountain View, CA, with a hybrid schedule (at least 3 days per week in office). The position reports to the LiDAR performance lead. What You'll Do Work with electrical, mechanical, manufacturing, and reliability engineers to develop and characterize high-performance LiDAR systems and electro-optical subsystems. Develop bench characterization methods and physics-based software models to confirm designs meet performance goals. Create and maintain validation plans that follow the design lifecycle from prototype to mass production. Define and support testing and calibration procedures to ensure LiDAR data quality at scale. Collaborate with design and test teams to set up testing methodologies and performance acceptance criteria. Design and carry out LiDAR field measurements and structured tests. Assess how environmental conditions impact LiDAR performance, and create strategies to detect and resolve quality issues using experimental design, data mining, and analysis. Work closely with LiDAR software, perception software, and systems engineers to resolve field data quality issues and help define requirements that ensure the LiDAR module meets system-level performance and safety standards. Move between physics modeling, simulation, large-scale data analysis, and hands-on prototyping as needed.

Who We Are Nuro is at the forefront of self-driving technology, dedicated to making autonomous driving accessible to everyone. Established in 2016, we are engineering the world’s most scalable driving solution by merging advanced AI with automotive-grade hardware. Our proprietary technology, the Nuro Driver™, is licensed to support a variety of applications, from robotaxis and commercial fleets to personal vehicles. With years of successful self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to achieving commercial-scale autonomous vehicles, fostering a safer, more connected future. About the Work Design and enhance state-of-the-art generative models, particularly focusing on diffusion architectures, flow-matching techniques, and energy-based models for autonomous planning. Develop generative models utilizing foundation models. Harness large language models and world foundation models for reasoning, decision-making, and multi-modal generation. Optimize generative models through reinforcement learning to enhance interactive reasoning. Investigate reward modeling and learned verifiers using generative models. Explore joint prediction and planning as well as self-play, and leverage generative models for active learning and world modeling. Create controllable generative models to direct the generation process towards specific goals, conditions, and rewards. Collaborate with autonomy teams to propose and implement holistic solutions to pressing autonomy challenges. Assess issues, suggest solutions, prioritize tasks, and evaluate your findings by deploying models on the Nuro Driver.