While expertise in fine-tuning LLMs is a requirement, a nice-to-have is that you have experience training multimodal models, vision and/or audio models.
Strong programming skills in languages such as Python
Expert knowledge of general language benchmarks (e.g., IFEval, BBH, MMLU-PRO) and how to develop custom metrics / benchmarks.
Experience with AI/ML frameworks (e.g. PyTorch, Scikit-learn, Axolotl) and deep learning libraries (e.g., Keras, OpenCV).
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker).
Understanding of data structures, algorithms, and software design patterns.
Design, develop, and deploy scalable, high-performance AI/ML models using popular frameworks such as PyTorch, or Scikit-learn.
Collaborate with Arcee’s research team to develop and refine AI/ML models, ensuring alignment with business requirements and customer needs.
Implement model serving, monitoring, and maintenance strategies to ensure reliability and performance.
Integrate AI/ML models with our products and solutions, ensuring seamless interaction with other components and systems.
Develop and maintain APIs, data pipelines, and data processing workflows to support AI/ML model deployment.
Collaborate with engineering teams to ensure AI/ML system scalability, reliability, and performance.
Deploy and debug our existing AI/ML infrastructure, including containerization (e.g., Docker), orchestration (e.g., Kubernetes), and cloud services (e.g., AWS SageMaker, GCP AI Platform).
Evaluate and implement new AI/ML tools and technologies, ensuring alignment with business needs and technical requirements.
Stay up-to-date with the latest AI/ML trends, research, and technologies, identifying opportunities for innovation and growth.
Participate in R&D initiatives, exploring new AI/ML applications, models, and techniques that can drive business value.