Job Description
Are you ready to shape the future of intelligence? Nexus Future Labs is seeking a visionary Senior AI Engineer to lead our next-generation Generative AI initiatives. As we race toward the technological breakthroughs of 2026, we need an expert who can bridge the gap between theoretical models and production-grade applications. Join a team dedicated to revolutionizing how humans interact with machines through advanced Large Language Models (LLMs) and autonomous agents.
In this role, you will be at the forefront of the AI revolution, deploying scalable models that drive business value and redefine user experiences. If you are passionate about Deep Learning, NLP, and building the cognitive architectures of tomorrow, we want to hear from you.
Responsibilities
- Model Development & Fine-tuning: Design, train, and fine-tune large-scale LLMs (e.g., GPT-4, Llama 3, Claude) using custom datasets to achieve high accuracy and domain-specific performance.
- RAG Architecture: Architect and optimize Retrieval-Augmented Generation pipelines to ensure real-time, context-aware responses for enterprise applications.
- Performance Optimization: Implement techniques such as quantization, pruning, and distillation to reduce latency and cost while maximizing inference throughput.
- MLOps Implementation: Build robust CI/CD pipelines for model deployment, ensuring continuous integration and monitoring of model performance in production environments.
- Cross-Functional Leadership: Collaborate with product managers, data scientists, and engineering teams to translate complex AI requirements into technical roadmaps.
- Ethical AI Compliance: Ensure all AI systems adhere to safety guidelines, bias mitigation protocols, and regulatory standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Programming: Proficiency in Python, PyTorch, TensorFlow, or JAX with deep experience in implementing neural network architectures.
- LLM Expertise: Hands-on experience with state-of-the-art foundation models, fine-tuning methodologies, and prompt engineering.
- Experience: 5+ years of experience in AI/ML engineering, with a proven track record of deploying successful machine learning products.
- Vector Databases: Strong understanding of vector embeddings, semantic search, and database technologies like Pinecone, Milvus, or pgvector.
- Problem Solving: Ability to debug complex distributed systems and optimize algorithms for edge cases.