Roles & Responsibilities:
Designing and Optimizing Large Language Models:
- Develop and fine-tune large language models tailored for specific applications.
Collaboration with MLOps Engineer:
- Work closely with MLOps engineers to prototype custom solutions, ensuring seamless integration with existing systems.
AI/ML Modeling Expertise:
- Demonstrate hands-on experience in AI/ML modeling, particularly with complex datasets.
- Possess a strong understanding of the theoretical foundations of AI/ML.
Production Environment Management:
- Efficiently manage large language models in production environments to enable (almost) real-time solutions.
ML Pipeline Development and Deployment:
- Build and execute ML pipelines, deploying models to enhance the accuracy of various process steps.
Competencies:
Natural Language Processing (NLP) Experience:
- Practical experience in NLP or a similar role.
Cloud Services Proficiency:
- Hands-on experience with ML cloud services on Azure or AWS, such as Azure ML, Amazon SageMaker, or MLFlow.
Programming Skills:
- Strong programming skills in languages like Python or Java.
Data Processing Expertise:
- Experience in large-scale data processing, including data collection, cleaning, and preprocessing.
UNIX/Linux Proficiency:
- Proficient in working with UNIX/Linux environments and command-line tools.
Analytical and Problem-Solving Skills:
