AI Fund
Machine Learning Engineer - Fine Tuning
AI Fund, San Francisco, California, United States, 94199
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Machine Learning Engineer - Fine Tuning
role at
AI Fund .
Ensure all your application information is up to date and in order before applying for this opportunity. About Baseten Join our dynamic team at Baseten, where we’re revolutionizing AI deployment with cutting-edge inference infrastructure. Backed by premier investors such as...
The Role As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you'll create value by leveraging our infrastructure to fine-tune large language models and other modalities, working directly with customers to meet their goals. Responsibilities include building scalable pipelines, implementing parameter-efficient techniques, and ensuring seamless inference. This customer-facing role requires technical expertise and the ability to translate customer needs into solutions. You'll also help shape our product roadmap by identifying common patterns and working with product teams to develop reusable components, streamlining the fine-tuning process.
Responsibilities
Design fine-tuning strategies to meet customer requirements, optimizing data preparation, training, and evaluation methods.
Develop tools for non-ML experts to fine-tune models effectively.
Implement scalable fine-tuning pipelines for large models and other AI modalities.
Work with customers to understand requirements and guide technical implementation.
Serve as the technical point of contact during the fine-tuning process.
Utilize state-of-the-art parameter-efficient fine-tuning methods (LoRA, QLoRA).
Build systems for data preparation, evaluation, and deployment of fine-tuned models.
Research and apply techniques in instruction tuning and model customization.
Create frameworks to evaluate model performance against base models.
Implement distributed training techniques like FSDP and DDP across hardware configurations.
Requirements
Bachelor’s degree in Computer Science, Engineering, or related field.
3+ years of ML engineering experience focused on model training and fine-tuning.
Experience with fine-tuning frameworks such as Axolotl, Unsloth, Transformers, TRL, PyTorch Lightning, or Torch Tune.
Hands-on experience with fine-tuning or pre-training LLMs or foundation models.
Excellent communication skills for explaining complex concepts.
Nice to Have
Experience working with customers to deliver solutions.
Track record of ML projects for enterprise clients.
Knowledge of distributed training and optimization techniques.
Experience with advanced alignment methods (RLHF, DPO, etc.).
Knowledge of prompt engineering and domain adaptation.
Contributions to open-source fine-tuning tools.
Experience building user interfaces for fine-tuning workflows.
Experience with cloud platforms and containerization.
Benefits
Competitive compensation, flexible PTO, healthcare coverage.
Opportunity to be part of a rapidly growing startup in AI.
Inclusive culture fostering learning and growth.
Exposure to ML startups for learning and networking.
If you’re motivated and passionate about ML, apply now to shape the future of AI! Baseten is committed to diversity and inclusion, providing equal opportunities regardless of background.
Additional Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and IT
Industries: Venture Capital and Private Equity
#J-18808-Ljbffr
Machine Learning Engineer - Fine Tuning
role at
AI Fund .
Ensure all your application information is up to date and in order before applying for this opportunity. About Baseten Join our dynamic team at Baseten, where we’re revolutionizing AI deployment with cutting-edge inference infrastructure. Backed by premier investors such as...
The Role As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you'll create value by leveraging our infrastructure to fine-tune large language models and other modalities, working directly with customers to meet their goals. Responsibilities include building scalable pipelines, implementing parameter-efficient techniques, and ensuring seamless inference. This customer-facing role requires technical expertise and the ability to translate customer needs into solutions. You'll also help shape our product roadmap by identifying common patterns and working with product teams to develop reusable components, streamlining the fine-tuning process.
Responsibilities
Design fine-tuning strategies to meet customer requirements, optimizing data preparation, training, and evaluation methods.
Develop tools for non-ML experts to fine-tune models effectively.
Implement scalable fine-tuning pipelines for large models and other AI modalities.
Work with customers to understand requirements and guide technical implementation.
Serve as the technical point of contact during the fine-tuning process.
Utilize state-of-the-art parameter-efficient fine-tuning methods (LoRA, QLoRA).
Build systems for data preparation, evaluation, and deployment of fine-tuned models.
Research and apply techniques in instruction tuning and model customization.
Create frameworks to evaluate model performance against base models.
Implement distributed training techniques like FSDP and DDP across hardware configurations.
Requirements
Bachelor’s degree in Computer Science, Engineering, or related field.
3+ years of ML engineering experience focused on model training and fine-tuning.
Experience with fine-tuning frameworks such as Axolotl, Unsloth, Transformers, TRL, PyTorch Lightning, or Torch Tune.
Hands-on experience with fine-tuning or pre-training LLMs or foundation models.
Excellent communication skills for explaining complex concepts.
Nice to Have
Experience working with customers to deliver solutions.
Track record of ML projects for enterprise clients.
Knowledge of distributed training and optimization techniques.
Experience with advanced alignment methods (RLHF, DPO, etc.).
Knowledge of prompt engineering and domain adaptation.
Contributions to open-source fine-tuning tools.
Experience building user interfaces for fine-tuning workflows.
Experience with cloud platforms and containerization.
Benefits
Competitive compensation, flexible PTO, healthcare coverage.
Opportunity to be part of a rapidly growing startup in AI.
Inclusive culture fostering learning and growth.
Exposure to ML startups for learning and networking.
If you’re motivated and passionate about ML, apply now to shape the future of AI! Baseten is committed to diversity and inclusion, providing equal opportunities regardless of background.
Additional Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and IT
Industries: Venture Capital and Private Equity
#J-18808-Ljbffr