Software Engineer (Training Product)

Baseten; United States; Remote; USD 180,000 - 230,000; Full time

Benefits offered by this job

Remote-first culture

In-person team summits three times a <

Job summary

Baseten is seeking a software engineer to ship developer-focused ML infrastructure. You will design and implement features across API, backend, and infra, enabling multi-node training, checkpointing, and seamless deployment of checkpoints to inference servers.

You will collaborate with research engineers to apply state-of-the-art training techniques, iterate rapidly, and deliver user-friendly tooling. You’ll work from a remote-friendly setup, with opportunities to join in-person summits and

Qualifications

• 5+ years of building software applications
• Experience building developer tooling or infrastructure products
• Excellent written and verbal communication
• Deep knowledge of web stack, databases, and distributed systems
• Interest in ML/AI infrastructure and willingness to learn

Responsibilities

• Own features from conception to MVP and GA
• Architect solutions across API, backend, database, infra, and frontend
• Fine-tune models to understand user workflows
• Collaborate with research engineers on training techniques
• Improve training DX and pipeline reliability
• Fix bugs and respond to customer issues with urgency

Skills

5+ years experience

Developer tooling/infrastructure

Strong communication

Web stack & distributed systems

ML/AI infrastructure interest

Product sense for dev tools

Model training methods (Fine-Tuning,RL

Open source training stacks

Distributed training (DeepSpeed)

Frontend fluency

Tools

NCCL

PyTorch

Megatron

DeepSpeed

HF Trainer

Job description

• 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
• 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

Benefits

• Remote-first work environment. The Baseten team is welcome to work from wherever they want; fully remote, in our San Francisco office, or a mix of both. Today, our team (including our founding team) is spread across the United States, Canada, and Armenia. We provide a $1,000 stipend for you to make your home-office comfortable and productive
• Regular in-person team summits. We get together as a team three times a year to plan, workshop, and most importantly, get to know each other better
• Unlimited PTO. We ask that everyone take at least 4 weeks of vacation. And we have a company-wide break between Christmas and New Year’s Day
• Full healthcare coverage. Medical, dental and vision insurance for you and your family
• Paid parental leave. 16-weeks fully paid parental leave (adoptive and non-birth parents included) and flexibility with schedules while returning to work
• Company-sponsored 401(k) for you to contribute to
• Learning and development budget. We encourage you to take classes, attend conferences, and invest in your craft and we’ll cover expenses to make it happen

Driven by high agency and ownership5+ years experience building software applicationsExperience developing developer tooling or infrastructure products for external or internal usersStrong communication skills with the ability to bridge technical depth and business needsDeep knowledge of the web stack, databases, and distributed systemsInterest in ML/AI infrastructure and willingness to learnGood taste in product, particularly developer-oriented toolsExperience with model development methods and paradigms, like Supervised Fine-Tuning, Reinforcement Learning, Synthetic Data Generation, LoRA, Full Finetunes, etcExperience launching features and products through different release cycles (MVP, Beta, GA, 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 agentsFrontend fluencyIf 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