ML Engineer: LoRA/QLoRA Production Pipelines

Baasi Inc.; Austin (TX); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive compensation

Equity potential

Flexible remote work

Job summary

A stealth-mode startup in Austin, Texas is seeking an AI ML Engineer (Python) to design and implement AI pipelines for their next-generation infrastructure. This role focuses on productizing existing fine-tuning techniques, automating data preprocessing, and collaborating with a technical team. The ideal candidate will have strong Python skills, experience with PyTorch, and familiarity with LoRA/QLoRA methods. Join us for competitive compensation and flexible remote work opportunities.

Qualifications

• Strong programming skills in Python.
• Hands-on experience with PyTorch and Hugging Face ecosystem.
• Familiarity with LoRA/QLoRA or parameter-efficient fine-tuning methods.
• Understanding of mixed precision training (FP16/BF16) and memory optimization techniques.
• Experience building training scripts that are production-ready.
• Comfortable working in Linux GPU environments.

Responsibilities

• Implement and maintain LoRA/QLoRA fine-tuning pipelines using PyTorch + Hugging Face Transformers + PEFT.
• Develop logic for incremental training and adapter stacking.
• Automate data preprocessing for user-supplied datasets.
• Build training scripts/workflows that integrate with orchestration backends.
• Implement monitoring hooks for dashboards.
• Collaborate with DevOps to ensure reproducible training environments.

Skills

Python

PyTorch

Hugging Face ecosystem

Linux GPU environments

LoRA/QLoRA

MLOps

Job description

A stealth-mode startup in Austin, Texas is seeking an AI ML Engineer (Python) to design and implement AI pipelines for their next-generation infrastructure. This role focuses on productizing existing fine-tuning techniques, automating data preprocessing, and collaborating with a technical team. The ideal candidate will have strong Python skills, experience with PyTorch, and familiarity with LoRA/QLoRA methods. Join us for competitive compensation and flexible remote work opportunities.