AI Developer

Key Skills

Aartificial intelligence, AWS, Azure, BERT, C++, Google Cloud Platform (GCP), GPT, Java Programming, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Python Programming, Scrum Agile Methodology

Job Description

Key Responsibilities

• Develop, and optimize generative AI models with a strong focus on RAG and Graph RAG.
• implement end-to-end generative AI solutions, from data preparation to production deployment
• Develop custom AI models and fine-tune pre-trained models for specific client use cases
• Optimize generative models for production, balancing performance, latency
• Design and implement efficient data pipelines for training and serving generative models
• Develop strategies for effective prompt engineering and few-shot learning in production systems
• Implement robust evaluation frameworks for generative AI outputs
• Address challenges related to bias, fairness, and ethical considerations in generative AI applications
• Develop internal tools and frameworks to accelerate generative AI development

Technical Skills

Required

• Strong programming skills in languages such as Python, Java, or C++
• Solid understanding of machine learning algorithms and techniques
• Demonstrated experience with large language models (LLMs) transformers such as GPT, BERT, T5, etc.
• Practical understanding of generative AI frameworks (e.g., Hugging Face Transformers, OpenAI GPT, DALL-E)
• Familiarity with prompt engineering and few-shot learning techniques
• Familiar with MLOps and LLMOps practices, including CI/CD for ML models
• Strong knowledge of one or more cloud-based AI services (e.g., AWS Bedrock, Azure ML, Google Vertex AI)
• Deep understanding of state-of-the-art AI architectures (e.g., Transformers, VAEs, GANs, Diffusion Models)
• Proficiency in Python and software engineering best practices for AI systems

Preferred

• Proficiency in optimizing generative models for inference (quantization, pruning, distillation)
• Experience with distributed training of large-scale AI models
• Advanced Techniques: Experience with reinforcement learning, unsupervised learning, or graph-based learning models.
• Agile Methodologies: Experience working in Agile/Scrum environments.
• Version Control: Proficiency with Git and other version control systems.

Impact You'll Make:

Qualifications

• Advanced degree in Computer Science, Machine Learning, or related field with a focus on generative models
• 2+ years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing generative AI pilots, proofs of concept, and prototypes

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.