Machine Learning Engineer - LLM Fine-tuning and Performance

Job Overview

As a Machine Learning Engineer (LLM Fine-tuning & Performance Specialist), you will play a crucial role in enhancing the accuracy and performance of fine-tuned Large Language Models (LLMs) for real-world applications. This groundbreaking opportunity allows you to work with cutting-edge ML technologies, collaborating closely with partners to drive innovation and ensure smooth integration and deployment of ML solutions. Your expertise will be essential in automating ML workflows and optimizing performance, making a lasting impact in the field of AI.

Key Responsibilities

• Develop, implement, and manage processes for optimizing LLMs using domain-specific data, improving the model's capability to complete structured tasks.
• Develop and implement techniques to measure LLM performance, defining and monitoring metrics such as recall, F1, perplexity, BLEU, ROUGE, etc.
• Utilize tools like ONNX and TensorRT for optimizing model inference on specialized hardware.
• Collaborate with ISVs and IHVs to understand their performance requirements and ensure successful model integration.
• Use C++ to improve ML model performance, specifically in performance-critical systems, and provide technical mentorship to junior engineers.

Qualifications

• 8+ years of validated experience in system software or related field.
• M.S. or higher degree in Computer Science/Data Science/Engineering or equivalent experience.
• Deep understanding of transformer architectures and large language models like GPT, BERT, T5, or similar.
• Validated hands-on experience with fine-tuning LLMs for specific tasks and improving model performance using libraries like PyTorch.
• Strong ability to assess and optimize model performance using relevant metrics and evaluation techniques.
• Proficiency in crafting and automating ML workflows using tools such as Kubeflow, MLflow, or Airflow.
• Excellent problem-solving skills, especially in debugging and improving LLM accuracy for real-world applications.
• Proficiency in Python and knowledge of C++ for optimizing performance and developing system-level integrations.
• Strong interpersonal skills for effective collaboration with internal teams and external partners.

Preferred Qualifications

• Experience with LLM-based function and tool calling systems.
• Understanding of distributed training for LLM fine-tuning and cloud platforms like Nvidia's NVCF.
• Familiarity with hardware acceleration for ML workloads, including GPU and specialized hardware optimizations.

Compensation

The base salary range is $180,000 - $339,250 USD annually. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.

Diversity and Inclusion

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Application Process

NVIDIA accepts applications on an ongoing basis. Join us in shaping the future of AI and computing.

Job ID: JR1990034