Job Description
Shape the Future of Intelligence
Nexus AI is at the forefront of the Generative AI revolution. We are seeking a visionary Generative AI Engineer to architect the next generation of Large Language Models (LLMs) and multimodal AI systems. If you are passionate about pushing the boundaries of what is possible with AI and want to work in an environment that prioritizes innovation and impact, we want to hear from you.
Key Responsibilities:
In this pivotal role, you will be responsible for the entire lifecycle of our AI models—from research and development to deployment and monitoring. You will work directly with our lead data scientists and product managers to build scalable, reliable, and ethical AI solutions.
Qualifications:
We are looking for a candidate with a strong foundation in both computer science and machine learning principles. You should be comfortable navigating ambiguity and have a track record of delivering high-quality code in fast-paced environments.
Responsibilities
- Design and implement state-of-the-art Generative AI models and inference pipelines using Python and PyTorch.
- Develop and optimize Retrieval-Augmented Generation (RAG) architectures to improve model accuracy and reduce hallucinations.
- Perform rigorous model evaluation, hyperparameter tuning, and bias mitigation to ensure ethical AI deployment.
- Collaborate with cross-functional teams to translate complex AI capabilities into intuitive user experiences.
- Deploy and manage AI workloads on Kubernetes and cloud-native environments (AWS/GCP).
- Stay abreast of the latest research in NLP and Deep Learning to integrate cutting-edge techniques into our production systems.
Qualifications
- 5+ years of experience in software engineering with a focus on Machine Learning or Artificial Intelligence.
- Deep proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
- Extensive experience fine-tuning and serving Large Language Models (e.g., Llama 3, GPT-4).
- Strong understanding of distributed systems, cloud computing, and containerization technologies.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
- Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).