Job Description
Quantum Dynamics is on a mission to redefine the boundaries of artificial intelligence. We are looking for a visionary Senior Generative AI Engineer to lead the development of our next-generation Large Language Model (LLM) products.
In this high-impact role, you will be at the forefront of the AI revolution, building scalable, efficient, and safe generative models that power enterprise solutions. You will work in a collaborative environment with top-tier researchers and engineers, pushing the envelope of what's possible in natural language processing.
Join us and help shape the future of intelligent automation.
Responsibilities
- Design and implement state-of-the-art Retrieval-Augmented Generation (RAG) pipelines to minimize hallucinations and enhance factual accuracy.
- Optimize LLM inference latency and reduce operational costs through model quantization, pruning, and distillation strategies.
- Collaborate with cross-functional teams to integrate generative AI capabilities into our core SaaS products and customer-facing APIs.
- Curate, clean, and fine-tune large-scale datasets for model training and continuous improvement.
- Establish robust evaluation frameworks and monitoring systems to track model performance and drift in production environments.
- Mentor junior engineers and conduct technical code reviews to maintain high engineering standards.
- Stay ahead of the curve by researching emerging trends in transformer architectures, multimodal AI, and synthetic data.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related technical field (or equivalent extensive practical experience).
- 5+ years of professional experience in software engineering with a strong focus on AI/ML and deep learning.
- Expert proficiency in Python, PyTorch, or TensorFlow, with deep knowledge of Hugging Face Transformers and DeepSpeed.
- Proven experience deploying and optimizing LLMs (e.g., GPT-4, Llama 2/3, Mistral) in production environments.
- Strong understanding of vector databases (e.g., Pinecone, Weaviate, Milvus) and RAG architectures.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile development environment.