Machine Learning Engineer - Fine Tuning

Reposted 22 Days Ago
2 Locations
In-Office
150K-225K Annually
Mid level
Software
The Role
The Machine Learning Engineer will fine-tune models, develop scalable pipelines, work with customers, and implement advanced training techniques.
Summary Generated by Built In

ABOUT BASETEN

Baseten powers inference for the world's most dynamic AI companies, like OpenEvidence, Clay, Mirage, Gamma, Sourcegraph, Writer, Abridge, Bland, and Zed. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. With our recent $150M Series D funding, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we’re scaling our team to meet accelerating customer demand.

THE ROLE

As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you'll create exceptional value for customers by leveraging our world-class infrastructure to fine-tune large language models and/or other modalities, working directly with customers to achieve their specific goals. 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 also 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 precisely 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.

  • This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era.

  • An inclusive and supportive work culture that fosters learning and growth.

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If 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.


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.

Top Skills

AWS
Axolotl
Azure
GCP
PyTorch
Pytorch Lightning
Torch Tune
Transformers
Trl
Unsloth
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The Company
59 Employees

What We Do

At Baseten we provide all the infrastructure you need to deploy and serve ML models performantly, scalably, and cost-efficiently.

Get started in minutes, and avoid getting tangled in complex deployment processes. You can deploy best-in-class open-source models and take advantage of optimized serving for your own models.

We also utilize horizontally scalable services that take you from prototype to production, with light-speed inference on infra that autoscales with your traffic.

Best in class doesn't mean breaking the bank. Run your models on the best infrastructure without running up costs by taking advantage of our scaled-to-zero feature

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