Baseten에서 AI 모델 학습 플랫폼을 고도화할 소프트웨어 엔지니어를 채용합니다. 분산 시스템 및 웹 스택에 대한 깊은 이해를 바탕으로 멀티 노드 학습 및 서버리스 RL 기능을 설계합니다. 5년 이상의 경력과 개발자 도구 구축 경험이 필수이며, AI 인프라에 대한 열정을 가진 분을 찾습니다.
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.
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!
Take a look at what we’ve built so far:
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.
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
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
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
Competitive compensation, including meaningful equity.
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
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).
