Senior Software Engineer - Model Training at Baseten

San Francisco, California, United States

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$200,000 – $275,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine LearningIndustries

Requirements

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, or similar) 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

Responsibilities

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

Skills

distributed training

FSDP

DDP

ZeRO

mixed precision training

GPU optimization

fine-tuning

foundation models

scalable pipelines

system design

Baseten

Platform for deploying and managing ML models

About Baseten

Baseten provides a platform for deploying and managing machine learning (ML) models, aimed at simplifying the process for businesses. Users can select from a library of open-source foundation models and deploy them with just two clicks, making it easier to implement ML solutions. The platform features autoscaling, which adjusts resources based on demand, and comprehensive monitoring tools for tracking performance and troubleshooting. A key differentiator is Baseten's open-source model packaging framework, Truss, which allows users to package and deploy custom models easily. The company operates on a usage-based pricing model, where clients pay only for the time their models are actively deployed, helping them manage costs effectively.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$58.4MTotal Funding

SERIES_BCompany Stage

AI & Machine LearningIndustries

51-200Employees

Benefits

💰 Competitive compensation: We aim to provide 90th percentile (or better) salaries and equity grants for every team member commensurate with their experience.

🌎 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. 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.

📈 401(k): 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.

Risks

Increased competition from specialized AI models tailored for specific industries.

Potential over-reliance on Google Cloud Marketplace may limit flexibility and control.

Rapid AI model development could render Baseten's offerings obsolete without continuous innovation.

Differentiation

Baseten offers a serverless backend for machine-learning applications with auto-scaling.

Truss, an open-source model packaging framework, allows seamless deployment of custom models.

Baseten's platform provides comprehensive monitoring tools for efficient model performance tracking.

Upsides

Integration with Google Cloud Marketplace boosts visibility and customer acquisition potential.

$40M Series B funding enhances Baseten's platform capabilities and market reach.

Chains framework positions Baseten for complex AI workflows, attracting sophisticated projects.

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