Job Description
We are seeking a visionary Senior AI & Machine Learning Engineer to join our elite research division. At Nexus Future Labs, we are building the next generation of cognitive systems designed to reshape industries by 2026 and beyond. If you are passionate about pushing the boundaries of Deep Learning, Large Language Models (LLMs), and Neural Architecture Search, this is your opportunity to lead high-impact projects in a cutting-edge environment.
You will work alongside world-class researchers and engineers to architect scalable AI solutions, optimize inference pipelines, and deploy state-of-the-art models to production. This role offers a competitive compensation package, comprehensive benefits, and the chance to define the future of intelligent automation.
Responsibilities
- Design, train, and fine-tune large-scale Generative AI models (e.g., GPT, LLaMA, Claude variants) for enterprise applications.
- Implement and optimize complex Deep Learning architectures using PyTorch and TensorFlow to improve model accuracy and reduce latency.
- Lead the end-to-end deployment of AI models into cloud infrastructure (AWS/GCP) using containerization and MLOps best practices.
- Collaborate with cross-functional teams to translate business requirements into robust technical AI solutions.
- Conduct rigorous research on emerging Neural Network techniques and integrate novel approaches into our product suite.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related technical field.
- Proven experience of 5+ years in Artificial Intelligence, Machine Learning, or Data Science.
- Expert proficiency in Python and experience with major ML frameworks (PyTorch, TensorFlow, JAX).
- Deep understanding of NLP, Transformer models, and prompt engineering strategies.
- Hands-on experience with vector databases (e.g., Pinecone, Milvus, Weaviate) and RAG architectures.
- Strong grasp of distributed computing, GPU optimization, and cloud infrastructure (AWS/GCP/Azure).