Job Description
We are at the forefront of technological evolution, building the cognitive engines of tomorrow. As a Senior AI Engineer at Nebula Dynamics, you will architect the next generation of autonomous agents and generative models that redefine enterprise intelligence. This is not just a coding role; it is an opportunity to lead the charge in deploying scalable, high-impact AI solutions in production environments.
Our culture is built on curiosity, radical transparency, and the relentless pursuit of excellence. We are looking for a visionary engineer who is passionate about Large Language Models (LLMs), prompt engineering, and the ethical application of artificial intelligence. If you thrive in a fast-paced, high-stakes environment and want to shape the future of AI, we want to hear from you.
Responsibilities
- Model Architecture & Training: Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) using transformer architectures and advanced deep learning frameworks.
- Production Optimization: Develop and optimize production pipelines for model inference, ensuring low latency, high throughput, and cost-effective resource utilization.
- RAG Implementation: Implement and refine Retrieval-Augmented Generation (RAG) strategies to enhance model accuracy, reduce hallucinations, and improve relevance.
- Collaborative Engineering: Partner with cross-functional teams of data scientists, product managers, and designers to translate complex business requirements into robust technical solutions.
- System Evaluation: Conduct rigorous testing and evaluation of model performance, including bias detection, safety alignment, and continuous improvement of model accuracy metrics.
- Scalability: Lead the design of scalable microservices and APIs that integrate AI models seamlessly into our broader software ecosystem.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent practical experience).
- Experience: 5+ years of professional experience in software engineering, with a strong focus on AI/ML, Deep Learning, or NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Knowledge: Deep understanding of neural network principles, optimization techniques, and the latest advancements in Generative AI.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Soft Skills: Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.