Baseten
Overview
Machine Learning Engineer - Fine Tuning at Baseten. This role focuses on fine-tuning large language models and other modalities, building scalable pipelines, and translating customer needs into effective solutions. It is a customer-facing technical role that also helps shape the product roadmap by identifying patterns in customer requirements. Base pay range
$150,000.00/yr - $225,000.00/yr About Baseten
Baseten powers inference for the world\'s most dynamic AI companies by uniting applied AI research, flexible infrastructure, and seamless developer tooling. We enable organizations to bring cutting-edge models into production. We are scaling our team to meet accelerating customer demand. The role
As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you\'ll create value for customers by leveraging our infrastructure to fine-tune large language models and/or other modalities. You\'ll build scalable pipelines, implement parameter-efficient techniques, and ensure a seamless transition to inference. This customer-facing role requires both technical expertise in foundation model adaptation and the ability to translate customer needs into effective solutions. You\'ll help shape our product roadmap by identifying common patterns in customer requirements and working with product teams to develop reusable components and features, reducing the need for custom services and streamlining the fine-tuning process for everyone. Responsibilities
Design comprehensive fine-tuning strategies that translate customer requirements into effective technical approaches—finding the optimal combination of data preparation, training techniques, and evaluation methods to deliver solutions that address customer needs Develop tools to enable non-ML experts to fine-tune models effectively Design and implement scalable fine-tuning pipelines for large language models and other AI modalities Work directly with customers to understand requirements and guide technical implementation Serve as the technical point of contact for customers throughout their fine-tuning journey Utilize state-of-the-art parameter-efficient fine-tuning methods (LoRA, QLoRA) Build systems for efficient data preparation, evaluation, and deployment of fine-tuned models Research and apply cutting-edge techniques in instruction tuning and model customization Create frameworks to evaluate fine-tuned model performance against base models Implement best-in-class distributed training techniques like FSDP and DDP across various hardware configurations Requirements
Bachelor’s degree in Computer Science, Engineering, or related field 3+ years of experience in ML engineering with focus on model training and fine-tuning Experience with advanced fine-tuning frameworks such as Axolotl, Unsloth, Transformers, TRL, PyTorch Lightning, or Torch Tune, enabling efficient model adaptation and optimization Hands-on experience fine-tuning or pre-training LLMs or other foundation models Excellent communication skills for explaining complex concepts to varied audiences NICE TO HAVE
Experience working with customers to deliver technical solutions Track record of delivering ML projects to enterprise customers Knowledge of distributed training systems and efficiency optimization techniques Experience with advanced alignment and adaptation techniques including RLHF, DPO, constitutional AI, prompt tuning, reinforcement learning with execution feedback, PPO, or other emerging alignment methods Knowledge of prompt engineering and domain adaptation methods Contributions to open-source fine-tuning projects or tools Experience building user-friendly interfaces for fine-tuning workflows Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies Benefits
Competitive compensation package Opportunity to be part of a rapidly growing startup in AI engineering Inclusive and supportive work culture that fosters learning and growth Exposure to a variety of ML startups, offering learning and networking opportunities Apply now to embark on a rewarding journey in shaping the future of AI. If you are motivated and passionate about machine learning and want to be part of a collaborative team, we would love to hear from you. Baseten is an equal employment opportunity employer. We provide equal 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. Compensation Range: $150K - $225K Seniority level
Not Applicable Employment type
Full-time Job function
Engineering and Information Technology Industries
Software Development Referrals increase your chances of interviewing at Baseten. Get notified about new Machine Learning Engineer jobs in New York, NY.
#J-18808-Ljbffr
Machine Learning Engineer - Fine Tuning at Baseten. This role focuses on fine-tuning large language models and other modalities, building scalable pipelines, and translating customer needs into effective solutions. It is a customer-facing technical role that also helps shape the product roadmap by identifying patterns in customer requirements. Base pay range
$150,000.00/yr - $225,000.00/yr About Baseten
Baseten powers inference for the world\'s most dynamic AI companies by uniting applied AI research, flexible infrastructure, and seamless developer tooling. We enable organizations to bring cutting-edge models into production. We are scaling our team to meet accelerating customer demand. The role
As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you\'ll create value for customers by leveraging our infrastructure to fine-tune large language models and/or other modalities. You\'ll build scalable pipelines, implement parameter-efficient techniques, and ensure a seamless transition to inference. This customer-facing role requires both technical expertise in foundation model adaptation and the ability to translate customer needs into effective solutions. You\'ll help shape our product roadmap by identifying common patterns in customer requirements and working with product teams to develop reusable components and features, reducing the need for custom services and streamlining the fine-tuning process for everyone. Responsibilities
Design comprehensive fine-tuning strategies that translate customer requirements into effective technical approaches—finding the optimal combination of data preparation, training techniques, and evaluation methods to deliver solutions that address customer needs Develop tools to enable non-ML experts to fine-tune models effectively Design and implement scalable fine-tuning pipelines for large language models and other AI modalities Work directly with customers to understand requirements and guide technical implementation Serve as the technical point of contact for customers throughout their fine-tuning journey Utilize state-of-the-art parameter-efficient fine-tuning methods (LoRA, QLoRA) Build systems for efficient data preparation, evaluation, and deployment of fine-tuned models Research and apply cutting-edge techniques in instruction tuning and model customization Create frameworks to evaluate fine-tuned model performance against base models Implement best-in-class distributed training techniques like FSDP and DDP across various hardware configurations Requirements
Bachelor’s degree in Computer Science, Engineering, or related field 3+ years of experience in ML engineering with focus on model training and fine-tuning Experience with advanced fine-tuning frameworks such as Axolotl, Unsloth, Transformers, TRL, PyTorch Lightning, or Torch Tune, enabling efficient model adaptation and optimization Hands-on experience fine-tuning or pre-training LLMs or other foundation models Excellent communication skills for explaining complex concepts to varied audiences NICE TO HAVE
Experience working with customers to deliver technical solutions Track record of delivering ML projects to enterprise customers Knowledge of distributed training systems and efficiency optimization techniques Experience with advanced alignment and adaptation techniques including RLHF, DPO, constitutional AI, prompt tuning, reinforcement learning with execution feedback, PPO, or other emerging alignment methods Knowledge of prompt engineering and domain adaptation methods Contributions to open-source fine-tuning projects or tools Experience building user-friendly interfaces for fine-tuning workflows Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies Benefits
Competitive compensation package Opportunity to be part of a rapidly growing startup in AI engineering Inclusive and supportive work culture that fosters learning and growth Exposure to a variety of ML startups, offering learning and networking opportunities Apply now to embark on a rewarding journey in shaping the future of AI. If you are motivated and passionate about machine learning and want to be part of a collaborative team, we would love to hear from you. Baseten is an equal employment opportunity employer. We provide equal 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. Compensation Range: $150K - $225K Seniority level
Not Applicable Employment type
Full-time Job function
Engineering and Information Technology Industries
Software Development Referrals increase your chances of interviewing at Baseten. Get notified about new Machine Learning Engineer jobs in New York, NY.
#J-18808-Ljbffr