Задачи:
— Разработка и поддержка кода с использованием AI-агентов (Claude Code, Cursor, OpenAI Codex и др.).
— Рефакторинг AI/ML и CV-компонентов в условиях гетерогенной среды (Go / C++ / Python).
— Быстрое прототипирование гипотез и внедрение новых алгоритмов.
— Интеграция ML-моделей в микросервисную архитектуру (gRPC / Kafka).
— Оптимизация инференса и работа с high-load системами.
Требования:
— Уверенный уровень Python, опыт разработки AI/Computer Vision решений.
— Знание алгоритмов (SuperPoint, NetVLAD, Gaussian Splatting), опыт работы с PyTorch, OpenCV.
— Практический опыт работы с AI Tools: Claude Code, Cursor, Antigravity или аналогами, понимание workflow VibeCoding.
— Опыт production-развёртывания ML-сервисов (FastAPI, Docker, gRPC), понимание микросервисной архитектуры (Kafka).
— Готовность работать в окружении с Go и C++ (чтение, интеграция, базовое понимание).
— Понимание и применение SDD (Specification-Driven) и TDD подходов.
— Умение быстро прототипировать и проверять гипотезы.
— Опыт работы с технической документацией и умение создавать её.
Преимущества:
— Опыт оптимизации inference для мобильных и серверных сред.
— Опыт работы с облачной инфраструктурой GCP.
— Понимание специфики AR/VR разработки.
Условия:
— Режим оформления: ТК/ИП
— Удаленная работа
— Гражданство РФ
Location: San Francisco; Toronto; New York; Montreal; Seattle
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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 Software Engineer at Baseten, you will own one of the most critical surfaces of our business: pricing, billing, and revenue infrastructure.
As we launch more and more products— billing is no longer just operational plumbing. It is a strategic lever for growth. This role will establish clear ownership of billing as a function and create leverage for Finance, Sales, and GTM teams while maintaining a seamless customer experience.
RESPONSIBILITIES
- Own Baseten’s end-to-end billing and revenue infrastructure, including pricing, invoicing, metering, and reporting foundations.
- Build and evolve our billing platform and integrations (including Orb), ensuring correctness, auditability, and a high-trust experience for customers and internal teams.
- Partner closely with Finance, Sales, GTM, and Forward Deployed Engineering to turn real-world workflows into reliable internal tooling and automation (quoting, approvals, renewals, usage reconciliation, revenue reporting).
- Design systems that scale with new products, packaging, and go-to-market motions, making billing a strategic lever for growth.
- Drive reliability and operational excellence for revenue-critical workflows: monitoring, alerting, incident response, backfills, and clear runbooks.
- Lead from the front on high-impact projects: clarify requirements, propose crisp technical approaches, ship iteratively, and raise the bar on quality and velocity.
- Debug and resolve production issues with urgency, communicating clearly with stakeholders and closing the loop with durable fixes.
REQUIREMENTS
- Bachelor's degree or higher in Computer Science or related field
- Experience with billing systems or building internal tools
- Deep knowledge of the web stack & databases
- Strong collaboration and communication skills
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
ГибридSan Francisco; Toronto; New York; Montreal; Seattle
Location: San Francisco; New York
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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 Solutions Architect at Baseten you will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. This role is a great fit for entrepreneurial, customer-facing technical professionals who want a front-row view into how modern companies adopt AI at scale, and who enjoy working across technical discovery, solution design, demos, deployment scoping, and hands-on customer implementations, in close partnership with Sales and Engineering.
RESPONSIBILITIES
- Partner with Sales on customer discovery calls (most often second calls, occasionally first calls for large accounts).
- Lead demos and technical scoping to align on success criteria, architecture, and deployment approach.
- Own benchmarking and repeatable deployments, including:
- Handling standard deployment patterns and configurations across many modalities – LLMs, embeddings, image and video generation, Voice AI, etc.
- Advising on tradeoffs like H100s vs B200s and latency-optimized vs throughput-optimized setups.
- Driving consistent “playbook” style deployments for common models and use cases.
- Become a power user of different runtimes such as vLLM, SGLang, and TRT-LLM and all the common configurations and tradeoffs between them
- Drive POC and project execution, including:
- Scoping POCs and keeping stakeholders aligned on timeline, deliverables, and next steps.
- Acting as the “ringleader” or project manager for POCs.
- Pulling in Forward Deployed Engineering (FDE) support when deeper or more complex technical work is needed.
REQUIREMENTS
- AI/ML background and the ability to credibly discuss AI/ML topics with technical stakeholders.
- Strong customer-facing communication skills, including the ability to run structured discovery and clarify ambiguous requirements.
- Technical depth to scope solutions, without needing to write production code.
- Ability to script and prototype as needed, including comfort “vibe coding” to move quickly in technical workflows.
NICE TO HAVE
- Experience running or supporting benchmarks for ML inference deployments.
- Familiarity with infrastructure tradeoffs relevant to inference performance and cost (for example GPU selection and latency versus throughput tuning).
- Experience serving as a cross-functional technical lead for customer POCs, including coordination across Sales and Engineering.
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Location: San Francisco; Toronto; New York; Montreal; Seattle
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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
At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations.
Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed.
In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts.
RESPONSIBILITIES
- Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack, helping us move beyond TCP/IP to unlock order-of-magnitude improvements in bandwidth and latency.
- Optimize Distributed Inference: You will implement and tune the networking layers necessary for efficient Disaggregated KV Cache Offload and WideEP, ensuring seamless communication across NVLink and InfiniBand for our MoE models.
- Enable Serverless-Grade Startup Speeds for LLMs: You will work deeply with checkpointing and storage mechanisms to enable sub-10-second startup for trillion-parameter models.
- Deep-Dive into Hardware: You will characterize and validate networking performance on bleeding-edge clusters (H100/H200, B200/B300, GB200/300 NVL72), writing the acceptance tests that ensure our hardware delivers peak achievable throughput and minimal latency.
- Build Observability: You will design the tools that let us visualize packet flow, congestion, and effective bandwidth across the GPU interconnects, helping us diagnose complex distributed system behaviors.
- Optimize Kernels: You will work with communication libraries (NCCL, NVSHMEM) and potentially write custom communication kernels to overlap compute and data transfer.
REQUIREMENTS
- You have deep experience with high-performance networking protocols (InfiniBand, RoCE v2) and understand the physics of data movement.
- You are fluent in C++ or Python, with the ability to bridge the gap between high-level logic and hardware. You have a deep understanding of the memory hierarchy in modern NVIDIA architectures (H100/Blackwell) and know how to optimize for it.
- You like going deep. You aren't afraid to dive into TensorRT-LLM source code, write custom C++ / Python bindings, or debug NVLink topology issues.
- You know when to use an off-the-shelf solution and when we need to build a custom solution because the upstream tools (like standard Kubernetes networking) are too slow for our needs.
NICE TO HAVE
- Deep knowledge of NCCL, NVSHMEM, and UCX.
- Experience with Rust for systems-level or performance-critical networking code is a strong plus
- Experience with GPUDirect Storage (GDS) or high-performance filesystems like Weka or 3FS.
- Familiarity with TensorRT-LLM, vLLM, or SGLang.
- Experience running low-level benchmarks to "qualify" new hardware clusters.
THE TEAM
- Bleeding Edge Hardware: We are preparing to bring Blackwell (B200/B300) and then Rubin architectures online. You will be one of the first engineers in the industry optimizing networking for NVL72/GB300 racks.
- We go deep: We operate at every depth. Whether it’s tuning hardware interconnects, writing custom communication kernels, or designing distributed inference strategies, we work across the entire stack to deliver performance that goes far and beyond.
- High Impact: The networking optimizations you build will directly enable features that no one else in the industry has fully mastered yet, like seamless multi-node WideEP and instant model hydration.
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Location: New York; San Francisco
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own.
The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will:
- Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal
- Contribute to open-source projects — members of the team are active contributors to SGLang — and publish technical content that demonstrates Modal's capabilities across the AI stack
- Collaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholder
- Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work
- Conduct technical demos, experiments, and proof-of-concepts that make Modal's performance advantages tangible
REQUIREMENTS:
- 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure
- Familiarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains. You don't need all of these, but you should be able to go deep on at least one.
- Strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership
- Genuine interest in working directly with customers — you find it energizing to understand someone else's problem and help them solve it
- Bonus: side projects, open-source contributions, or published work you're proud of in ML or systems performance
- Willing to work in-person in New York City, San Francisco, or Stockholm
Location: San Francisco; Stockholm; New York; London
Workplace: OnSite
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
Modal is hiring a high-impact Solutions Architect to drive technical strategy across our most strategic enterprise accounts.
You will operate as the executive technical counterpart to Enterprise Account Executives, leading complex evaluations, shaping infrastructure modernization roadmaps, and driving multi-product adoption across AI/ML workloads.
This role is not demo support. It is a strategic, consultative position requiring strong architectural depth, executive presence, and the ability to influence 7–8 figure infrastructure decisions. You will work directly with CTOs, VPs of Engineering, and ML platform leaders to help them rethink how AI infrastructure should be built and operated.
If you thrive in high-velocity technical sales environments and want to shape the infrastructure layer powering modern AI companies, this role is for you.
WHAT YOU’LL DO:
- Own the technical strategy for large, complex enterprise accounts
- Partner with Enterprise Account Executives to drive 6–7+ figure opportunities from qualification through close
- Lead deep technical discovery across platform, ML, DevOps, and infrastructure stakeholders
- Architect end-to-end migration strategies from AWS, GCP, or Azure to Modal’s serverless infrastructure
- Drive executive-level technical conversations that connect infrastructure architecture to business impact (velocity, cost efficiency, reliability)
- Design and oversee proof-of-concepts that demonstrate production-grade scalability and performance
- Navigate security reviews, compliance discussions, and procurement processes with confidence
- Build durable relationships with technical champions and executive sponsors
- Orchestrate cross-functional virtual account teams (Sales, Product, Engineering, Support) to ensure successful adoption
- Influence Modal’s product roadmap by surfacing structured enterprise feedback
- Mentor other Solutions Architects and contribute to technical best practices across the team
REQUIREMENTS:
- 5+ years in Solutions Engineering, Sales Engineering, or enterprise-facing technical roles in infrastructure, cloud, or developer platforms
- Demonstrated success driving complex enterprise sales cycles ($250K+ ACV; experience with $1M+ ARR accounts strongly preferred)
- Experience working with large, sophisticated Bay Area technology companies or global enterprises
- Deep expertise in cloud infrastructure (AWS, GCP, Azure) including compute, networking, storage, and managed services
- Strong architectural understanding of containers and orchestration (Docker, Kubernetes)
- Experience designing distributed systems and production data platforms
- Strong working knowledge of ML/AI infrastructure (training pipelines, inference systems, GPU workloads, MLOps)
- Experience leading cloud migration or infrastructure modernization initiatives
- Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD systems
- Production programming experience in Python strongly preferred
- Executive-level communication skills with the ability to influence technical and business stakeholders
- Proven ability to lead cross-functional virtual teams in high-stakes account environments
- Strong business acumen and understanding of enterprise procurement and buying processes
- Willingness to travel up to 30%
Задачи:
— Разрабатывать и внедрять ML-модели в областях Computer Vision и NLP.
— Развёртывать и оптимизировать inference-пайплайны на GPU-серверах.
— Работать над мультимодальными AI-фичами (текст, изображения, видео, аудио).
— Масштабировать производительность моделей под растущую базу пользователей.
— Сотрудничать с backend-инженерами над продакшн-API.
— Проводить эксперименты и A/B-тесты на основе реальных пользовательских данных.
Требования:
— 5+ лет практического опыта в ML/AI-разработке.
— Отличное знание Python и фреймворков PyTorch / TensorFlow.
— Глубокое понимание NLP (LLMs, embeddings, transformers) и CV (image generation, diffusion models, video processing).
— Опыт работы с GPU-обучением и inference.
— Навыки оптимизации моделей (quantization, distillation, batching, caching).
— Опыт продакшн-деплоя ML-сервисов.
— Будет плюсом: опыт работы с видео-AI моделями, понимание high-load inference систем, опыт с ML-мониторингом и аналитикой (Weights & Biases, MLflow, Grafana), опыт в сфере conversational AI или чатботов, участие в open-source, Kaggle или публикации в ML-сообществе.
Условия:
— Работа в международной продуктовой компании.
— Гибкий график и удалённый формат.
— Возможность влиять на ключевые продуктовые решения.
Location: Hybrid - San Francisco
About Vercel:
Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience.
Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide.
About the Role:
As a member of the AI Gateway Team, you will be responsible for developing and enhancing our AI Gateway platform, which provides a unified API for accessing hundreds of AI models from multiple providers. You will collaborate with a remote and distributed team of engineers to build reliable, low-latency systems that handle rate limiting, intelligent failovers, and seamless integrations, enabling developers to ship AI-powered applications without managing provider-specific complexities. This role focuses on ensuring production-ready reliability for AI workloads, including automatic fallbacks during outages and consistent performance across providers like OpenAI, Anthropic, Google, and more.
What You Will Do:
Contribute to the design, implementation, and maintenance of the AI Gateway platform, emphasizing features like unified API endpoints, rate limit management, and intelligent failover mechanisms to boost uptime and reliability.
Write clean, efficient, and well-documented code, conducting thorough testing to ensure low-latency responses and stability for high-volume AI inference requests.
Collaborate with cross-functional teams, including product managers, AI researchers, and infrastructure engineers, to integrate new AI providers and models while addressing scalability and performance challenges.
Engage with the open-source community, contribute to AI SDK and related projects, and align with Vercel's ethos of fostering developer tools.
Gather user feedback and analytics to drive innovations in AI Gateway, such as enhanced billing unification, provider-agnostic authentication, and analytics for usage insights.
About You:
5+ years of relevant experience
Strong proficiency in JavaScript/TypeScript and experience with backend development, APIs, and cloud infrastructure
Experience with AI/ML integrations, API gateways, distributed systems, or handling high-throughput services (e.g., rate limiting, caching, failovers)
Experience contributing to or participating in open source projects
Excellent communication skills and the ability to work effectively in a collaborative team environment
Benefits & Compensation:
Competitive compensation package, including equity.
Inclusive Healthcare Package.
Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
Flexible Time Off.
We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.
The San Francisco, CA base pay range for this role is $196,000-$294,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process.
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Equal Opportunity:
Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.
Location: New York
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization.
WHO YOU ARE:
You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answer itself.
RESPONSIBILITIES:
Team
- Recruit, hire, and grow a high-performing team of cloud platform engineers; run regular 1:1s focused on coaching, feedback, and career growth.
- Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work.
- Foster a culture of ownership, accountability, and continuous improvement.
Technical Direction
- Drive day-to-day technical decisions through design reviews, code reviews, and architectural discussions.
- Translate the infrastructure roadmap into clear team priorities and milestones, and hold execution against them.
- Establish standards for reliability, performance, and operational excellence; ensure the team owns projects end-to-end, from spec through production.
- Push for good judgment on tooling and architecture, with a bias against unnecessary complexity.
Cross-Functional & Incident Leadership
- Partner with product and engineering to align infrastructure work with business priorities; represent your team's progress, capacity, and tradeoffs clearly to leadership.
- Serve as the escalation point for major incidents; drive resolution with urgency and ensure the team learns systematically, feeding those learnings back into infrastructure improvements.
REQUIREMENTS:
- 10+ years of industry experience, including 3+ years in a leadership role
- Track record building high-performance distributed systems at scale
- Strong background in cloud infrastructure
- Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.)
- Proficiency in a systems-level language (Rust, C, C++, or Java)
Location: New York
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will:
- Drive in-depth quantitative analyses to inform our pricing and packaging strategy.
- Help spin up our deal desk and streamline enterprise deals.
- Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities.
- Implement new tools and processes to enable the GTM org to grow rapidly.
- Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan.
REQUIREMENTS:
We are looking for someone who:
- Has 5+ years experience working in some kind of business function (e.g. banking, consulting, startup).
- Has some exposure to tech and coding (in order to understand our product & customer, work with analytical tools, and build out custom tooling).
- Is analytical, organized and detail-oriented, holds their output to a high bar of excellence.
- Is eager to learn about a variety of different business functions and juggle many projects at once.
- Is excited about working in-person in NYC.
Location: San Francisco
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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 a Sales Manager to help lead a team of Strategic Account Executives. This person will be responsible for building and coaching a team of high-performing sales reps, driving revenue growth, and partnering closely with product and engineering to bring our cutting-edge AI infrastructure to customers.
RESPONSIBILITIES
- Lead and mentor a team of Strategic Account Executives to consistently exceed pipeline and revenue goals.
- Help define and execution on go-to-market strategy for our fastest growing customer segment.
- Collaborate cross-functionally with Marketing, Product, and Engineering to align customer needs with Baseten’s product roadmap.
- Be deeply engaged with the product, enabling reps to have highly technical conversations with prospects and customers.
- Foster a culture of accountability, learning, and collaboration within the sales team.
REQUIREMENTS
- 6+ years of closing sales experience, with 2+ years in management leading high-performing teams.
- Strong technical acumen, ideally with background in AI infrastructure, cloud infrastructure, or developer platforms.
- Comfortable operating in the weeds with technical products and guiding reps through complex deals.
- Proven track record of success in Strategic/Enterprise sales environments.
- Based in San Francisco or New York and open to coming in office at least 3 days per week (Tuesday-Thursday).
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Location: San Francisco; New York
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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 https://www.baseten.co/blog/baseten-training-is-ga/#training-is-now-ga
- Training docs overview https://docs.baseten.co/training/overview
- Story of the Training product https://www.baseten.co/blog/a-q-a-from-inference-to-training-the-inside-story-of-baseten-s-newest-product/
- Research we've done https://www.baseten.co/resources/research/
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 users to train large models like GLM 4.7 and DeepSeek. We’ve built deeply at the Kubernetes layer to ensure that scheduling, startup, inter-node communication, and shutdown happen seamlessly under the hood and as the user expects.
- Training DX: Customers come to train on Baseten because it helps them get to value fast. To do this, we ensure that the features we ship aren’t just fast, but are easy to iterate with. We enhanced Baseten’s metrics from pod-level GPU summaries to per-GPU and per-Node. We’ve built a CLI experience that caters to terminal users, and UI experiences that enable user to seamlessly manage their training jobs.
RESPONSIBILITIES
- Iterate like crazy
- Design ergonomic APIs and abstractions to model complex resources and lifecycles
- Work throughout the stack (API layer, backend and database implementation, infra layer; frontend is a plus) to implement features.
- Fine-tune and deploy models to develop intuition around training workflows.
- Partner closely with model developers and world-class research engineers to understand the requirements and pain points of post-training workflows.
- Drive long-term improvements to improve reliability of systems and velocity of development
- Fix bugs & resolve customer issues with urgency
REQUIREMENTS
- 5+ years experience building software applications
- Deep knowledge of the web stack, databases, and distributed systems
- Experience developing developer tooling or infrastructure products for external or internal users.
- Good taste in product, particularly developer-oriented tools
- Interest in ML/AI infrastructure and willingness to learn
- Driven by high agency and ownership
- Strong communication skills with the ability to bridge technical depth and business needs
NICE TO HAVE
- Experience launching features and products through different release cycles (MVP, Beta, GA, etc.)
- Experience with model development methods and paradigms, like Supervised Fine-Tuning, Reinforcement Learning, Synthetic Data Generation, LoRA, Full Finetunes, etc.
- Familiarity or experience with the open source training stack and frameworks (NCCL, PyTorch, Megatron, NemoRL, VeRL, Axolotl, HF Trainer) and distributed training techniques (FSDP, DeepSpeed).
- Experience developing AI products, tooling, or agents
- Frontend fluency
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Location: New York
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team.
This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include:
- Identifying architectural changes to improve reliability and performance.
- Fostering a culture of reliability across Modal’s engineering organization.
- Defining and implementing operational processes such as deployments, upgrades, etc.
- Operating systems like Kubernetes, Postgres, Redis, etc.
- Participating in on-call rotations, and responding to production incidents.
REQUIREMENTS:
- 5+ years of experience writing high-quality production code.
- 2+ years of on-call experience for critical production services.
- Strong cloud skills, and deep familiarity with at least one hyperscaler cloud (AWS preferred).
- Familiarity with auto scaling, fleet management, and capacity planning at scale.
- Experience operating databases, monitoring, CI/CD, and other infrastructure, at scale
- Experience owning and scaling Kubernetes clusters to thousands of nodes a plus.
- Experience with systems safety research (e.g. STAMP) and control theory a plus.
- Ability to work in-person in our NYC or Stockholm offices.
Location: Stockholm
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform.
REQUIREMENTS:
- 5+ years of experience writing high-quality production code
- Experience building high-performance distributed systems at a large scale (the more battle scars, the better)
- Strong cloud skills
- Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.)
- Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!)
- Ability to work in-person in our Stockholm office.
- Prior experience with Rust is nice to have, but not required.
- Ability to participate in on-call rotation and respond to production incidents.
Location: New York, NY (HQ); San Francisco, CA
Workplace: Hybrid
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
ABOUT THE ROLE
The Applied AI team at Ramp is at the forefront of leveraging AI to drive innovation across our platform. We are seeking strong full-stack engineers who are proficient in web frameworks, backend development, and infrastructure. You will work on exciting projects such as AI Agents, Retrieval-Augmented Generation, Structured Extraction (we made https://github.com/1rgs/jsonformer), internal tooling for customer-facing teams, fine-tuning models, and build infrastructure for LLM inference. If you're passionate about working on real production use cases of large language models (LLMs) and want to contribute to groundbreaking AI applications, this role is for you.
WHAT YOU’LL DO
- Ship full-stack AI projects end to end
- Build and integrate components for AI infrastructure, supporting production-level inference and fine-tuning
- Develop and improve engineering processes, tools, and systems to scale AI solutions across Ramp
- Create tools and internal platforms to enhance the productivity and capabilities of Ramp's AI and engineering teams
WHAT YOU NEED
- Proficiency in full-stack development, with a strong understanding of web frameworks, backend systems, and cloud infrastructure
- A track record of working on full-stack AI projects, particularly those involving production use cases of LLMs
- Experience building backend systems and infrastructure that can support AI-driven products
BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL)
- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- Weekly coffee stipend
UNITED STATES
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
- One Medical annual membership
- 401(k), including employer match on contributions made while employed by Ramp
- Fertility HRA (up to $10,000 per year)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
- Pet insurance
- In-office perks: lunch, snacks, drinks, and more
- Relocation expense coverage to NYC or SF (if needed)
CANADA
- Group medical, dental, and vision coverage through Sun Life
- Life, AD&D, and disability coverage
- Fertility drug coverage (up to $4,000 lifetime)
- Group Retirement Plan with employer match (RRSP + DPSP)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay
- Employee Assistance Program and virtual care through Lumino Health
UNITED KINGDOM
- Private medical insurance through Freedom Elite
- Virtual GP and at-home care via eMed x Livi
- Workplace pension through Penfold, with salary sacrifice option
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
REFERRAL INSTRUCTIONS
If you are being referred for the role, please contact that person to apply on your behalf.
OTHER NOTICES
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice
Location: Remote
Workplace: Remote
We are building AI to simulate the world through merging art and science.
We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.
World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.
Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.
ABOUT THE ROLE
We’re looking for Research Engineers to contribute to our ambitious research agenda spanning multimodal foundational models, interactive world modeling, and real-time generation. This role is highly collaborative and will touch many aspects of our broader research efforts, taking a full-stack approach across pretraining, SFT/RL post-training techniques, evaluation, and bringing models to production.
WHAT YOU’LL DO
- Run experiments to teach world models new behaviors — action following, scene manipulation, camera control, and beyond
- Develop and test new data strategies, architectural variants, and training techniques
- Design evaluations that measure model capabilities, and use them to drive model improvement
- Take features from research prototype to production, collaborating with product and creative teams to address application-specific gaps
- Contribute across the entire stack (data pipelines, modeling, production inference) to move projects forward
WHAT YOU’LL NEED
- 4+ years of experience in machine learning research or engineering
- Familiarity with the architecture, training, and inference of large-scale multimodal generative models
- Experience building robust data pipelines for pretraining and post-training
- Comfort working across the full research stack: data, training, evaluation, and deployment
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and experience with distributed training at scale
- Ability to context-switch quickly and drive projects forward in a fast-moving, ambiguous environment
- Excitement about building AI that simulates the world
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
WORKING AT RUNWAY
Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you.
We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.
More about Runway
- Universal World Simulator https://runwayml.com/world-simulator.html
- GWM-1 https://runwayml.com/research/introducing-runway-gwm-1
- Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5
- General World Models https://runwayml.com/research/introducing-general-world-models
- Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section
- Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section
- Runway Studios https://runwayml.com/studios
We're excited to be recognized as a best place to work:
Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024
Location: San Francisco
Workplace: OnSite
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day.
REQUIREMENTS:
- Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building.
- Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics.
- Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models.
- Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads.
- Strong product instincts; you think about customer problems, not just tickets.
- Ability to participate in on-call rotation and respond to production incidents.
- Ability to make good tradeoffs between shipping fast and building for scale.
- Ability to work in-person in our NYC or SF office.
Location: San Francisco; Toronto; New York; Montreal; Seattle
Workplace: Hybrid
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 https://www.baseten.co/blog/announcing-our-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 testing via CI/CD pipelines to catch regressions and build release workflow automation for the model runtimes stack.
- Optimization Automation: Build tools to find the "Pareto frontier"—identifying the absolute best configuration (latency vs. cost vs. quality) for a given model and workload.
REQUIREMENTS
This is a mid-senior, high leverage role. We care about your technical depth, strong communication skills to drive cross-team efforts, ability to navigate vague requirements and mentor other engineers. We want to talk to you if you have:
- A Love for Systems & Hardware: You aren’t just interested in the AI; you want to understand GPU memory subsystems, InfiniBand, and how data moves across a cluster.
- An Automation Mindset: You believe that if a task has to be done twice, it should be scripted. You have a passion for stress-testing and fuzzy testing to find the "breaking point" of a system.
- Mathematical Curiosity: A desire to understand the underlying math of Transformers and how it translates into FLOPs and memory requirements.
- Technical Toolkit: Familiarity with Python, and an eagerness to master the NVIDIA software stack. C++ familiarity is good to have.
WHY THIS ROLE
- Direct Impact: Your tools will be the gatekeeper for what defines "good" performance for our customers.
- Deep Learning (Literally): You will gain world-class expertise in GPU orchestration and LLM inference that few engineers in the industry possess.
- High Ownership: As the lead of a small team, you will have the autonomy to build tools from scratch and contribute to open-source projects.
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
ГибридSan Francisco; New York
165 000 – 330 000 $
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