Applied Ai Architects Manager Jobs

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are seeking an experienced and proactive Security Engineer to help us build, maintain, and continuously improve the security posture of our rapidly growing ML infrastructure platform. As one of the first dedicated security hires at Baseten, you will work cross-functionally with engineering and operations teams to ensure we’re meeting the highest standards of confidentiality, integrity, and availability. You’ll have an opportunity to shape our security strategy and best practices from the ground up, influencing the way our platform handles sensitive data for both internal and external stakeholders. RESPONSIBILITIES Security architecture and design: Collaborate with engineering teams to design and implement secure systems and infrastructure, including cloud (AWS/GCP) environments and container orchestration platforms. Vulnerability management: Lead proactive vulnerability assessments, pen tests, and remediation efforts to ensure our products and infrastructure remain secure. Incident response: Develop and maintain incident response processes, including detection, analysis, containment, eradication, and post-incident reviews. Identity and access management (IAM): Oversee IAM strategies and tools to ensure the right people have the right level of access to our systems and data. Security compliance and audits: Work closely with operations to ensure compliance with relevant standards (e.g., SOC 2, ISO 27001) and as

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. We are looking for an engineer with strong experience in machine learning and solid foundations in math and computer science to join our growing Post-Training team at Baseten. THE ROLE Custom models are instrumental to the success of Baseten customers. By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten. The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs. Your role as a research engineer is to build the in-house tooling to support all of this. We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale. At times this involves zooming deep into a particular technical topic, but more often it involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH Dense, on-policy or both? Repeated kv cache for

About the Team: GTM Innovation’s mission is to automate 100% of digital knowledge work for OpenAI's GTM so sellers spend more time directly with customers applying their strategy and judgment. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. The team builds and scales a fleet of virtual coworkers that operate as full-time employees and move increasingly ambitious tasks from the foreground to the background. About the Role We’re looking for a product-minded backend engineer to build the systems behind a new generation of AI coworkers: persistent agents that understand their environment, take on meaningful work, and improve over time. You’ll design and ship the foundational infrastructure that makes these agents effective in production, from durable workflow orchestration to long-running agent loops built on the Codex harness to the context, memory, tools, and permissions model they need to act reliably. You’ll also build rigorous evaluation, observability, and feedback systems that make agent quality measurable and continuously improve how these systems perform. This is a hands-on, high-ownership role at the intersection of agent infrastructure, applied AI, and product engineering. You’ll work directly with go-to-market teams and collaborate across OpenAI’s product and research organizations to turn ambiguous, real-world needs into dependable systems that help OpenAI meet the world at scale. In this role, you will: Build and scale durable agent runtimes, long-running agent loops, and workflow orchestration using the Codex harness and emerging agent infrastructure. Design context and memory systems that ground agents in the information they need while preserving clear access boundaries. Develop rigorous evaluation frameworks, production feedback loops, and observability to measure agent quality and improve it over time. Partner directly

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enabling

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are looking for Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Automate performance

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Baseten’s Model Performance (MP) team is responsible for ensuring the models running on our platform are fast, reliable, and cost‑efficient. As part of this team, you’ll focus on Model APIs — the infrastructure powering our hosted API endpoints for the latest open‑source models. This work spans distributed systems, model serving, and developer experience. You’ll join a small, high‑impact team operating at the intersection of product, model performance, and infra, helping to define how developers interact with AI models at scale. RESPONSIBILITIES: Design, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups Productionize performance improvements across runtimes with deep understanding of their internals: speculative decoding implementations, guided generation for structured outputs, custom scheduling and routing algorithms for high-performance serving Build comprehensive benchmarking frameworks that measure real-world performance across different model architectures, batch sizes, sequence lengths, and hardware configurations Productionize performa

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating deployments and monitoring systems to optimizing performance and managing incidents. We all work closely with our users, learning from their past struggles in operationalizing ML, onboarding them onto our platform, and turning our learnings into ideas for improving Baseten. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Build and maintain scalable infrastructure to support the deployment and operation of machine learning models. Establish standards and best practices for reliability and performance across the infrastructure. Automate processes when relevant, particularly for managing CI/CD pipelines. Own products and projects end-to-end, functioning as both an engineer and a project manager, with a focus on user empathy, project specification, and end-to-end execution. Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions. Mentor junior team members and contribute to knowledge sharing within the organization. Navigate ambiguity and exercise good judgment on tradeoffs and to

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact. RESPONSIBILITIES Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fund

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE The largest, most demanding enterprises are starting to run on Baseten, and they arrive with a range of security, compliance, and procurement requirements. As an Engineer on Baseten's enterprise engineering team, you'll build the capabilities that enable large organizations like Writer, HubSpot, and Notion to succeed on Baseten. Enterprise engineering authors the core building blocks, APIs, and user experiences powering the Baseten platform: identity and access management, billing, regional isolation, and self-hosted and single-tenant deployment options. This is deep product and systems work across the full stack, from designing authentication and authorization systems using standards like OAuth and OIDC to shipping the admin experiences enterprise IT teams use to manage their organization. EXAMPLE INITIATIVES Recent and upcoming work on the team: Fine-grained authorization for users, service accounts, and agentic workloads SSO and SCIM support, allowing customers to centralize and automate access to Baseten Expanding the billing platform to support evolving pricing models, advanced data exports, and controls to manage spend In-product management and enforcement of customer compliance requirements like data residency and HIPAA Securing network paths in and out of a customer's models with private connectivity and ingress and egress restrictions Allowing customers to run Baseten inside their own VPC, on-prem, or a

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions. We are seeking a Senior Machine Learning Engineer to help build and scale Entrata’s applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Implem

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact. RESPONSIBILITIES Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fund

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containerizati

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As an Engineer on the Dedicated Inference team, you'll shape the state-of-the-art developer experience for deploying and operating AI workloads in production. From the CLI and SDKs to APIs, observability, and debugging workflows, you'll build the tools customers rely on every day to manage mission-critical inference deployments. Few teams at Baseten have as much breadth and visibility as Dedicated Inference. The team is often at the forefront of new product development, giving engineers the opportunity to shape the experience of some of our most important customers. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Dedicated Inference team: Chains for multi-component workflows Asynchronous inference Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Implement new features and products for the team Design ergonomic APIs and abstractions to solve customer problems Fix bugs and resolve customer issues with urgency Work across the stack - regardless of where you start, you’ll end up touching both React Components and Kubernetes Pods Work closely with the product and forward deployed engineering teams to develop and drive new product ideas REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Python, Go, or JavaScript proficiency is a

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues. Apply and scale optimization techniques across a wide range of ML models, particularly large language models. Collaborate with a diverse team to design and implement innovative solutions. Own projects from idea to production. REQUIREMENTS Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. Experience with one