Job Description
We are seeking a visionary Senior AI/ML Engineer to join our team and help architect the artificial intelligence solutions of 2026. At Neural Nexus Inc., we are pushing the boundaries of what is possible with Generative AI, creating systems that are not only intelligent but also ethical, scalable, and transformative.
In this role, you will lead the development of next-generation Large Language Models (LLMs) and autonomous agents. You will work in a high-performance environment focused on research, training, and deployment of cutting-edge machine learning models. If you are passionate about the future of AI and want to build systems that solve complex problems for millions of users, we want to hear from you.
Responsibilities
- Design, train, and fine-tune state-of-the-art Generative AI models (e.g., GPT, Llama, Claude) to achieve high performance benchmarks.
- Architect scalable MLOps pipelines for model training, evaluation, and deployment using cloud infrastructure (AWS/GCP).
- Conduct rigorous research to improve model accuracy, reduce hallucinations, and enhance reasoning capabilities.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to integrate AI features into consumer products.
- Ensure ethical AI practices, including bias mitigation, data privacy, and responsible AI governance frameworks.
- Optimize inference latency and cost efficiency for large-scale model serving.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
- 5+ years of experience in machine learning engineering, specifically with Deep Learning and NLP.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of transformer architectures, attention mechanisms, and fine-tuning techniques.
- Experience with vector databases (Pinecone, Milvus) and RAG (Retrieval-Augmented Generation) architectures.
- Strong knowledge of distributed training and high-performance computing (HPC) clusters.
- Track record of publishing in top-tier AI conferences or delivering production-level AI products.