Machine Learning Engineer - Fine Tuning at Baseten

San Francisco, California, United States

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$150,000 – $225,000Compensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial IntelligenceIndustries

Requirements

Candidates should possess a Bachelor’s degree in Computer Science, Engineering, or a related field, along with at least three years of experience in Machine Learning Engineering, specifically focusing on model training and fine-tuning. Experience with advanced fine-tuning frameworks like Axolotl, Unsloth, Transformers, TRL, and familiarity with parameter-efficient techniques such as LoRA and QLoRA is required.

Responsibilities

The Machine Learning Engineer - Fine Tuning will design comprehensive fine-tuning strategies to translate customer requirements into effective technical approaches, developing scalable pipelines for large language models and other AI modalities. They will work directly with customers to understand their needs, guide technical implementation, and serve as the technical point of contact throughout the fine-tuning journey. Additionally, this role involves researching and applying cutting-edge techniques in instruction tuning and model customization, creating frameworks for efficient data preparation, evaluation, and deployment, and implementing best-in-class distributed training techniques.

Skills

Machine Learning Engineering

Model Training

Fine-tuning

Axolotl

Unsloth

Transformers

TRL

LoRA

QLoRA

Data Preparation

Model Deployment

Technical Communication

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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