Machine Learning Engineer – Fine Tuning

Machine Learning Engineer – Fine Tuning

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

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

Preferred Qualifications

• 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