Software Engineer, Network Models

Role overview Meter Inc. is developing tools to capture and preserve the expertise of network engineers. The team’s goal is to build systems that document how experts diagnose network issues, making it possible for future models to manage networks with less manual effort. This work will help Meter support many customer networks while reducing the need for direct engineer intervention. What makes this work unique Network engineering lacks the structured archives found in software development. While Git and GitHub record software decisions, the reasoning behind network troubleshooting often disappears once a problem is fixed. This role centers on building a structured, searchable system for network operations, a kind of GitHub for network engineering. The system will capture network state, expert observations, and the logic behind key decisions. Your first 90 days First 30 days: Meet with network engineers to learn their workflows. Study what effective diagnostic documentation looks like and identify the necessary data. Review telemetry (ClickHouse), configurations (Postgres), and support history (Salesforce). By 60 days: Deliver a working annotation interface. Network engineers should be able to review past support tickets, view the network’s state during incidents, and record their reasoning. The tool should be practical and encourage regular use. By 90 days: Network engineers will be able to create training data independently. Initial model benchmarks from your pipeline will be live, showing how your work improves the process. Technical stack TypeScript React Go GraphQL Kafka Postgres Collaboration This role works closely with Meter’s co-founder and CEO, who will help guide the product roadmap and set priorities. Location This position is based in San Francisco.

About MeterAt Meter, we believe that networking is at the heart of technological advancement. We have innovatively unified the entire networking stack and are now on a mission to make it autonomous.Our team is developing a cutting-edge neural network-driven system designed to analyze raw computer networks, enabling us to address all networking challenges. As outlined on Meter.ai, we are creating models within a closed-loop system that utilizes real-time telemetry, logs, and network events to autonomously troubleshoot issues, enhance performance, and resolve challenges.To achieve this, we require not only exceptional models but also robust infrastructure that ensures our models have clean, versioned, and low-latency access to the necessary data throughout training, evaluation, and deployment phases.Why this Role is EssentialEach Meter network deployed in the field serves as a valuable data source for our Models team. However, without meticulous infrastructure design, this data risks becoming fragmented, outdated, or inconsistent. In this role, you will ensure that such pitfalls are avoided. You will be responsible for the core data interface that drives our model development, experimentation, evaluation, and real-time inference.This position is fundamental and offers a significant impact. Your contributions will shape the speed at which we can train new models, the reliability of their evaluations, and their seamless operation across hundreds of real-world networks. You will collaborate closely with modelers to deliver systems that are elegant, scalable, and robust.Your ResponsibilitiesDesign and implement the Models API: a unified interface for accessing training, evaluation, and deployment data across raw, transformed, and feature-engineered layers.Ensure backward compatibility and feature versioning across continually evolving schemas.Develop scalable pipelines to ingest, transform, and serve petabytes of data across Kafka, Postgres, and Clickhouse.Create CI/CD workflows that evolve the API in tandem with changes to the underlying data schema.Facilitate fine-grained querying of historical and real-time data for any network, at any point in time.Help establish and promote the principle of 'smart data, dumb functions': maximizing operations in the data layer to minimize downstream code complexity.Collaborate with modelers to co-design training frameworks that optimize performance.

ABOUT BASETENAt Baseten, we are at the forefront of AI innovation, providing critical inference solutions for leading AI companies like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. Our platform combines advanced AI research, adaptable infrastructure, and intuitive developer tools, empowering organizations to deploy state-of-the-art models effectively. With rapid growth and a recent $300M Series E funding round backed by top-tier investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we invite you to join our mission in building the platform of choice for engineers delivering AI products.THE ROLE:As a member of Baseten’s Model Performance (MP) team, you will play a pivotal role in ensuring our platform’s model APIs are not only fast and reliable but also cost-effective. Your primary focus will be on developing and optimizing the infrastructure that supports our hosted API endpoints for cutting-edge open-source models. This role involves working with distributed systems, model serving, and enhancing the developer experience. You will collaborate with a small, dynamic team at the intersection of product development, model performance, and infrastructure, defining how developers interact with AI models on a large scale.RESPONSIBILITIES:Design, develop, and maintain the Model APIs surface, focusing on advanced inference features such as structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multi-modal serving.Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, create custom CUDA operators, and enhance memory allocation patterns for maximum efficiency across multi-GPU setups.Implement performance improvements across various runtimes based on a deep understanding of their internals, including speculative decoding, guided generation for structured outputs, and custom scheduling algorithms for high-performance serving.Develop robust benchmarking frameworks to evaluate real-world performance across diverse model architectures, batch sizes, sequence lengths, and hardware configurations.Enhance performance across runtimes (e.g., TensorRT, TensorRT-LLM) through techniques such as speculative decoding, quantization, batching, and KV-cache reuse.Integrate deep observability mechanisms (metrics, traces, logs) and establish repeatable benchmarks to assess speed, reliability, and quality.

About Our TeamJoin the Inference team at OpenAI, where we leverage cutting-edge research and technology to deliver exceptional AI products to consumers, enterprises, and developers. Our mission is to empower users to harness the full potential of our advanced AI models, enabling unprecedented capabilities. We prioritize efficient and high-performance model inference while accelerating research advancements.About the RoleWe are seeking a passionate Software Engineer to optimize some of the world's largest and most sophisticated AI models for deployment in high-volume, low-latency, and highly available production and research environments.Key ResponsibilitiesCollaborate with machine learning researchers, engineers, and product managers to transition our latest technologies into production.Work closely with researchers to enable advanced research initiatives through innovative engineering solutions.Implement new techniques, tools, and architectures that enhance the performance, latency, throughput, and effectiveness of our model inference stack.Develop tools to identify bottlenecks and instability sources, designing and implementing solutions for priority issues.Optimize our code and Azure VM fleet to maximize every FLOP and GB of GPU RAM available.You Will Excel in This Role If You:Possess a solid understanding of modern machine learning architectures and an intuitive grasp of performance optimization strategies, especially for inference.Take ownership of problems end-to-end, demonstrating a willingness to acquire any necessary knowledge to achieve results.Bring at least 5 years of professional software engineering experience.Have or can quickly develop expertise in PyTorch, NVidia GPUs, and relevant optimization software stacks (such as NCCL, CUDA), along with HPC technologies like InfiniBand, MPI, and NVLink.Have experience in architecting, building, monitoring, and debugging production distributed systems, with bonus points for working on performance-critical systems.Have successfully rebuilt or significantly refactored production systems multiple times to accommodate rapid scaling.Are self-driven, enjoying the challenge of identifying and addressing the most critical problems.

At Hover, we empower individuals to design, enhance, and safeguard their cherished properties. Utilizing proprietary AI technology built on over a decade of real property data, we provide answers to pressing questions such as “What will it look like?” and “What will it cost?” Homeowners, contractors, and insurance professionals depend on Hover to receive fully measured, accurate, and interactive 3D models of any property—achieved through a smartphone scan in mere minutes.We are driven by curiosity, purpose, and a collective commitment to our customers, communities, and each other. At Hover, we believe the most innovative ideas stem from diverse perspectives, and we take pride in fostering an inclusive, high-performance culture that encourages growth, accountability, and excellence. Supported by leading investors like Google Ventures and Menlo Ventures, and trusted by industry leaders including Travelers, State Farm, and Nationwide, we are transforming how people perceive and interact with their environments.Why Join Hover?At Hover, 3D models are not just a feature; they are the essence of our product. Each scan and data point we process empowers homeowners, insurers, and contractors to make informed, data-driven decisions. We are seeking a Software Engineer who has a passion for geometry, automation, and making a tangible impact in the real world. In this role, you will design and implement systems that convert customer-captured imagery into meticulously accurate 3D models, enhancing the scalability and precision of Hover’s modeling pipeline. You will work collaboratively with designers and engineers across frontend, backend, computer vision, and DevOps to bring innovative capabilities to fruition, blending technical expertise with strong communication and cross-functional collaboration.The 3D Modeling Pipeline team develops the tools essential for our in-house operations to transform customer-captured scans into highly detailed, accurate 3D models of buildings. This team is also responsible for creating the pipeline and systems that process 3D data through both automated and manual steps, as well as exporting data into customer-facing formats.Your Contributions Will Include:Owning and evolving backend systems that convert raw scan data into exact 3D models, ensuring timely delivery to key ecosystem partners like Xactimate and Cotality.Building and refining internal modeling tools that enable teams to efficiently generate, validate, and optimize high-quality 3D data.Collaborating with machine learning and computer vision engineers to implement new algorithms into production, bridging research with practical applications.Enhancing customer and partner experiences by improving how Hover’s 3D outputs integrate with downstream workflows and external platforms.Promoting innovation and ongoing enhancement across our modeling pipeline.

OpenAI is seeking a Software Engineer in San Francisco to focus on improving productivity by optimizing model performance. This position centers on developing solutions that make machine learning models more efficient and effective. Role overview This role involves working closely with teams across different functions to identify and address areas where model performance can be improved. The aim is to deliver changes that have a measurable impact on both systems and workflows. What you will do Collaborate with engineers and other specialists to enhance model efficiency Develop and implement solutions that improve the effectiveness of machine learning systems Contribute to projects that streamline processes and drive productivity gains Impact Your work will help shape improvements in how models operate and how teams at OpenAI achieve their goals. The changes you help deliver will support more effective use of resources and better outcomes for the organization.

OpenAI’s networking teams design and manage high-performance systems that support the company’s training and inference infrastructure. As a Software Engineer focused on productivity, this position centers on making those teams more effective by improving the developer experience and streamlining complex workflows. Role overview This role supports engineers working on intricate infrastructure, with a focus on build systems, testing architecture, release pipelines, and overall development efficiency. The work involves optimizing how engineers build, test, validate, and deploy changes in environments that span multiple servers and interact closely with hardware. What you will do Improve development workflows for engineers building and operating networking systems at OpenAI. Design and refine pipelines for continuous deployment, release, and validation. Create and maintain test harnesses for multi-server, networked, and hardware-backed environments. Increase iteration speed across codebases, particularly in C++, Python, and environments centered on build systems. Work with engineers to identify and resolve pain points in CI, testing, debugging, and deployment processes. Lead testing and reliability strategies for infrastructure components that support large-scale training and inference workloads. Collaborate with both centralized developer experience teams and networking engineers who work directly with these systems.

At Databricks, we are dedicated to empowering data teams to tackle the most challenging problems in the world — from realizing the future of transportation to fast-tracking medical innovations. We accomplish this by developing and operating the premier data and AI infrastructure platform, enabling our customers to harness profound data insights for business enhancement. Our Model Serving product equips organizations with a cohesive, scalable, and governed solution for deploying and managing AI/ML models — ranging from traditional machine learning to intricate proprietary large language models. It ensures real-time, low-latency inference, governance, monitoring, and lineage. As the adoption of AI surges, Model Serving stands as a fundamental component of the Databricks platform, allowing customers to operationalize models at scale with robust SLAs and cost efficiency. In the role of Staff Engineer, you will significantly influence both the product experience and the core infrastructure of Model Serving. Your responsibilities will include designing and constructing systems that facilitate high-throughput, low-latency inference across CPU and GPU workloads, steering architectural strategies, and collaborating extensively with platform, product, infrastructure, and research teams to create an exceptional serving platform.

ABOUT BASETENAt Baseten, we are at the forefront of enabling transformative AI solutions for some of the world's leading companies, including Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. Our innovative platform combines cutting-edge AI research, adaptable infrastructure, and developer-friendly tools to facilitate the production of advanced models. Recently, we celebrated our rapid growth with a successful $300M Series E funding round from notable investors like BOND, IVP, Spark Capital, Greylock, and Conviction. We invite you to join our dynamic team and contribute to the evolution of AI product deployment.THE ROLEAs a Senior Software Engineer specializing in Model Training at Baseten, you will play a pivotal role in constructing the infrastructure essential for the large-scale training and fine-tuning of foundational AI models. Your responsibilities will include designing and implementing distributed training systems, optimizing GPU utilization, and establishing scalable pipelines that empower Baseten and our clientele to adapt models with efficiency and reliability. This role demands a high level of technical expertise and hands-on involvement: you will be responsible for critical components of our training stack, collaborate with product and infrastructure teams to identify customer needs, and drive advancements in scalable training infrastructure.EXAMPLE WORK:Training open-source models that surpass GPT-5 capabilities for a leading digital insurerExploring specialized, continuously learning models as the future of AIOverview of our training documentationResearch initiatives we've undertakenRESPONSIBILITIESDesign, construct, and sustain distributed training infrastructures for large foundation modelsDevelop scalable pipelines for fine-tuning and training across diverse GPU/accelerator clustersEnhance training performance through optimization of algorithms and infrastructureCollaborate closely with cross-functional teams to align technical solutions with business objectivesStay abreast of advancements in the field of machine learning and AI to continually improve our training processes

At Databricks, we are dedicated to empowering data teams to tackle some of the most challenging issues of our time—from realizing the future of transportation to speeding up medical innovations. We achieve this by developing and maintaining the premier data and AI infrastructure platform, allowing our clients to leverage profound data insights to enhance their operations. Our Model Serving product equips organizations with a cohesive, scalable, and governed platform for deploying and overseeing AI/ML models, spanning traditional ML to specialized large language models. It provides real-time, low-latency inference, governance, monitoring, and lineage capabilities. With the rapid rise of AI adoption, Model Serving stands as a fundamental component of the Databricks platform, enabling clients to operationalize models efficiently and cost-effectively at scale. As a Senior Engineer, your role will be pivotal in transforming both the product experience and the underlying infrastructure of Model Serving. You will design and create systems enabling high-throughput, low-latency inference across CPU and GPU workloads, influence architectural strategies, and work closely with platform, product, infrastructure, and research teams to deliver an exceptional serving platform.

Join Cloudflare as a Senior Software Engineer in our Network Development team, where you will design and implement innovative network solutions that enhance our global infrastructure. This role offers the opportunity to work with cutting-edge technologies and collaborate with talented engineers to drive significant improvements in network performance and reliability.

Astranis is at the forefront of satellite technology, creating cutting-edge satellites for high orbits that extend humanity's reach into the solar system. Our satellites are dedicated to providing secure networks for sophisticated clients worldwide, including large corporations, government entities, and the US military. With five satellites already in orbit and a robust pipeline of upcoming launches, we are addressing a commercial contract backlog exceeding $1 billion.Astranis stands out as the preferred satellite communication partner for clients with critical needs for uptime, data security, network visibility, and tailored solutions. We have successfully raised over $750 million from top-tier investors like Andreessen Horowitz, Blackrock, and Fidelity, and we proudly employ a talented team of 450 engineers and innovators at our expansive 153,000 sq. ft. headquarters in Northern California, USA.Embedded Software Engineer - Network SoftwareAs an Embedded Software Engineer on the Network Software team at Astranis, you will play a pivotal role in designing, developing, and implementing the flight software that commands and monitors our spacecraft. You will also have the opportunity to mentor junior engineers and collaborate cross-functionally to ensure the compatibility of the software with various hardware platforms.This position supports both commercial and US Government projects.RoleDevelop software for the Flight Computer and Earth Stations Hub for our satellites.Create firmware for control boards on the satellites and Earth Stations Hub.Enhance software reliability through requirements generation, continuous integration, automated testing, and code reviews.Collaborate with multiple teams including Payload, Communications Ground Control, and Telemetry.Utilize C++ to interface with the Flight computer and engage with custom hardware on the vehicle.Deliver complex projects through an incremental development approach.Requirements2-4+ years of experience in software development using modern C++ or C.Familiarity with software development methodologies and design patterns.Experience with communication protocols such as TCP/IP, I2C, and SPI.Strong communication and writing skills.A passion for space technology.Experience in building high availability and high reliability systems.

Join Crusoe Technologies as a Principal Software Engineer specializing in Software-Defined Networking (SDN). In this pivotal role, you will lead the design and development of innovative networking solutions that leverage SDN technologies. You will work closely with cross-functional teams to enhance our networking capabilities and drive the future of our products.As a thought leader in SDN, you will be responsible for architecting scalable solutions, optimizing performance, and ensuring robust security across our network infrastructure. This is an exciting opportunity to impact the rapidly evolving tech landscape.

Software Engineer, Delivery Network Platform Join Zipline, where we are revolutionizing logistics with an autonomous delivery network. As part of the Delivery Network Platform team, you will develop the foundational systems that enable aircraft, sites, and infrastructure to operate seamlessly in live delivery scenarios. Your work will involve creating software solutions that provide operators with real-time insights and control, designing orchestration systems that manage fleet movements, and developing validation platforms to ensure the network's reliability as it scales. Your Responsibilities You will be responsible for software systems that are pivotal to fleet operations, including: Network Operating Center software for real-time visibility and interventions across aircraft, sites, missions, weather, and demand. Fleet orchestration systems for assignment, routing, scheduling, and rebalancing tasks. Maintenance and asset health systems linking issue detection to service readiness. Simulation and validation platforms to assess topology, load, and policy changes prior to production. Platform interfaces and configurable control planes that empower other teams to safely extend the network. Tackling Complex Challenges Unlike typical software roles focused on digital experiences, this position plays a critical role in managing a live autonomous logistics network. You'll address challenges such as: Maintaining an accurate real-time view of aircraft and essential site assets across the network. Ensuring the network remains operational amidst shifting demand, changing weather conditions, infrastructure issues, or capacity constraints. Creating user-friendly operator control interfaces that facilitate quick and accurate decision-making under pressure. Simulating potential future network behaviors to mitigate risks before they impact production. These systems directly affect operational performance. You will own significant components of the platform, make critical technical and product decisions, and have a substantial impact on the network's effectiveness. Team Dynamics Our team operates with a strong emphasis on ownership, trust, and high technical standards. Engineers are expected to identify significant problems, develop a clear vision for system functionality, and drive solutions from conception to production. Additionally, we encourage engineers to leverage AI tools to enhance exploration, implementation, and debugging processes while upholding strong engineering principles, judgment, and accountability.

At Databricks, we are driven by our commitment to empower data teams in tackling the world's most challenging problems — from transforming transportation solutions to accelerating medical advancements. Our mission revolves around constructing and maintaining the world's premier data and AI infrastructure platform, enabling our clients to harness deep data insights for enhanced business outcomes.Foundation Model Serving represents the API product designed for hosting and serving advanced AI model inference, catering to both open-source models like Llama, Qwen, and GPT OSS, as well as proprietary models such as Claude and OpenAI GPT. We welcome engineers who have experience managing high-scale operational systems, including customer-facing APIs, Edge Gateways, or ML Inference services, even if they do not have a background in ML or AI. A passion for developing LLM APIs and runtimes at scale is essential.As a Staff Engineer, you will play a pivotal role in defining both the product experience and the underlying infrastructure. You will be tasked with designing and building systems that facilitate high-throughput, low-latency inference on GPU workloads with cutting-edge models. Your influence will extend to architectural direction, working closely with platform, product, infrastructure, and research teams to deliver an exceptional foundation model API product.The impact you will have:Design and implement core systems and APIs that drive Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.Collaborate with product and engineering leaders to outline the technical roadmap and long-term architecture for workload serving.Make architectural decisions to enhance performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.Contribute directly to critical components within the serving infrastructure, from systems like vLLM and SGLang to developing token-based rate limiters and optimizers, ensuring seamless and efficient operations at scale.Work cross-functionally with product, platform, and research teams to transform customer requirements into dependable and high-performing systems.Establish best practices for code quality, testing, and operational readiness while mentoring fellow engineers through design reviews and technical support.Represent the team in inter-departmental technical discussions, influencing Databricks’ wider AI platform strategy.

Join Cloudflare as a Senior Software Engineer specializing in Network Performance & Reliability! In this role, you'll be at the forefront of enhancing the performance and stability of our global network, ensuring our customers benefit from unparalleled speed and reliability. You'll collaborate with experts across various teams to design and implement innovative solutions that optimize network operations.

Join Crusoe as a Staff Software Engineer specializing in Networking. In this critical role, you will design and implement innovative software solutions that enhance our networking infrastructure. You will collaborate with cross-functional teams to optimize performance and reliability, ensuring that our services run efficiently and securely.

Join our innovative team at Crusoe as a Senior Software Engineer specializing in Networking. In this critical role, you will develop cutting-edge software solutions that enhance our networking capabilities and support our mission of delivering efficient computing resources.Your expertise will contribute to building scalable and reliable network architectures, enabling us to serve our clients better. Collaborate with cross-functional teams and leverage your knowledge in software engineering to push the boundaries of technology.

Waymo is a pioneering company in autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has established the Waymo Driver—The World’s Most Experienced Driver™—with a mission to enhance mobility access and save lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be integrated across various vehicle platforms and applications. Having completed over ten million rider-only trips, our technology has driven more than 100 million miles on public roads and tens of billions in simulations across over 15 U.S. states.The Perception team is responsible for developing systems that learn the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles (AVs). We collaborate closely with downstream teams to optimize and integrate our work into the Waymo Driver, conduct research to solve real-world challenges, and work alongside research teams at Alphabet. With access to millions of miles of diverse driving data from various sensors, we empower engineers like you to (1) create methods for efficient continuous learning from extensive real-world data, (2) develop scalable models and training methodologies, (3) analyze real-world behaviors to create systems that can navigate complexities, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

Join Crusoe as a Software Engineer II specializing in SDN Networking. In this pivotal role, you will enhance our innovative solutions, ensuring the reliability and efficiency of our networking systems. Collaborate with cross-functional teams to design, develop, and implement advanced software solutions that drive performance and scalability.