Principal AI Research Engineer - LLMs & Generative AI (Remote)
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Key skills for this role
About the Role
A client of Quik Hire Staffing seeks a Principal AI Research Engineer to develop and deploy AI models, focusing on LLMs and generative AI. The role involves designing, training, and optimizing machine learning systems on a contractual basis.
Key Skills for This Role
Responsibilities
- Design, train, and deploy AI models using frameworks like TensorFlow or PyTorch to address specific business problems.
- Optimize existing models for performance, scalability, and inference latency in production environments.
- Collaborate with cross functional teams to integrate AI solutions into existing data pipelines and infrastructure.
- Conduct rigorous testing and validation to ensure model reliability, fairness, and compliance with technical standards.
- Document technical decisions, model performance metrics, and deployment processes for internal and external stakeholders.
Requirements
- Proficiency in Python and experience with AI/ML libraries such as TensorFlow, PyTorch, or scikit learn.
- Minimum of 3 years of hands on experience developing and deploying machine learning models in production.
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools for model lifecycle management.
- Ability to work autonomously in a remote setting with clear communication of technical progress and challenges.
Full Job Posting
Role Overview
- This role requires developing and deploying AI models to solve complex problems in a high impact domain.
- You will work independently on a contractual basis to design, implement, and optimize machine learning systems that deliver measurable business value.
- The work directly contributes to advancing AI capabilities in a fast moving technical environment.
Key Responsibilities
- Design, train, and deploy AI models using frameworks like TensorFlow or PyTorch to address specific business problems.
- Optimize existing models for performance, scalability, and inference latency in production environments.
- Collaborate with cross functional teams to integrate AI solutions into existing data pipelines and infrastructure.
- Conduct rigorous testing and validation to ensure model reliability, fairness, and compliance with technical standards.
- Document technical decisions, model performance metrics, and deployment processes for internal and external stakeholders.
Required Skills & Qualifications
- Proficiency in Python and experience with AI/ML libraries such as TensorFlow, PyTorch, or scikit learn.
- Minimum of 3 years of hands on experience developing and deploying machine learning models in production.
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools for model lifecycle management.
- Ability to work autonomously in a remote setting with clear communication of technical progress and challenges.
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