Baseten is hiring a Senior Software Engineer - Model Training

Baseten is looking for a Senior Software Engineer – Model Training to build the core infrastructure that powers large-scale training and fine-tuning of foundation models. In this role, you will design distributed systems, optimize GPU utilization, and create scalable pipelines that enable Baseten and our customers to adapt models efficiently.

What You'll Do

• Design, build, and maintain distributed training infrastructure for large-scale foundation models.
• Implement scalable pipelines for fine-tuning and training across heterogeneous GPU/accelerator clusters.
• Optimize training performance through techniques like FSDP, DDP, ZeRO, and mixed precision training.
• Contribute to frameworks and tooling that make training workflows efficient, reproducible, and developer-friendly.
• Collaborate with cross-functional teams (Product, Forward Deployed Engineering, Inference Infra) to ensure training systems meet real-world requirements.
• Research and apply emerging techniques in training efficiency and model adaptation, and productionize them in the Baseten platform.
• Participate in code reviews, system design discussions, and technical deep dives to maintain a high engineering bar.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience.
• 4+ years of experience in software engineering with a focus on ML infrastructure, distributed systems, or ML platform engineering.
• Hands-on expertise in distributed training frameworks (FSDP, DDP, ZeRO) and ML frameworks (PyTorch, Transformers, Lightning, TRL).
• Strong understanding of GPU/accelerator performance optimization and scaling techniques.
• Experience designing and operating large-scale systems in production (cloud-native preferred).
• Excellent problem-solving and communication skills, with the ability to work across infrastructure and ML boundaries.

Nice to Have

• Experience building APIs, SDKs, or developer tools for ML workflows.
• Familiarity with cluster management and scheduling (Kubernetes, Ray, Slurm).
• Knowledge of parameter-efficient fine-tuning methods (LoRA, QLoRA) and evaluation pipelines.
• Contributions to open-source distributed training or ML infra projects.
• Experience with cloud environments (AWS, GCP, Azure) and container orchestration.

Technical Stack

• ML Frameworks: PyTorch, Transformers, Lightning, TRL
• Training Techniques: FSDP, DDP, ZeRO
• Cluster Management: Kubernetes, Ray, Slurm
• Cloud Platforms: AWS, GCP, Azure

Team & Environment

You will collaborate with cross-functional teams including Product, Forward Deployed Engineering, and Inference Infrastructure.

Benefits & Compensation

• Competitive compensation package.
• An inclusive and supportive work culture that fosters learning and growth.
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

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.