Role Overview
We are looking for ML Engineers to join our team. In this role, you will build end-to-end ML systems, including data pipelines (with an emphasis on synthetic data generation), training, debugging, and performance analysis. You will also fine-tune large language models (LLMs), apply meta-learning techniques, and improve existing Nace.AI models by leveraging the latest research developments.
Key Responsibilities:
Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model training, debugging, and performance optimization.
Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model generalization and efficiency.
Improve existing Nace.AI models by incorporating advancements from recent ML research.
Qualifications:
2-4+ years of professional experience designing, training, and deploying large-scale machine learning models.
Proficient in Python with a strong track record of building substantial projects.
Solid foundation in computer science fundamentals (data structures, algorithms, design patterns).
BS degree in CS or related technical field.
Solid Experience with ML frameworks and libraries (PyTorch, TensorFlow).
Self-starter comfortable working in a fast-paced, dynamic environment.
Preferred Qualifications:
MS/PhD in CS or related technical field.
Prior experience in NLP, Diffusion Models, large language models (LLMs).
Familiarity with data processing stacks such as Spark and Airflow.
Experience with multi-node GPU training.
Contributor to open-source ML projects.
Send us your CV and code to career@nace.ai
