[Hiring] Machine Learning Engineer @Baseten
Apr 01, 2025 - Baseten is hiring a remote Machine Learning Engineer. 💸 Salary: unspecified. 📍Location: USA.
Role Description
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
Qualifications
- 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
Requirements
- 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 (Flexible PTO, covered healthcare premiums for you and your dependents)
- 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
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| 📍 | Be aware of the location restriction for this remote position: USA |
| ‼ | Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more. |
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Salary
💸
unspecified
|
Remote
Location
USA
|
|
Job Type
full-time
|
Posted
Apr 01, 2025
|
| 📍 | Be aware of the location restriction for this remote position: USA |
| ‼ | Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more. |
