Job Description
Are you ready to architect the next generation of Artificial Intelligence? Nexus Future Labs is seeking a visionary AI & Machine Learning Engineer to lead our research into Agentic AI and Autonomous Systems for the 2026 era.
In this role, you won't just implement existing models; you will pioneer the frameworks that will define the technological landscape of the coming decade. We are looking for individuals who are obsessed with scalability, ethics, and pushing the boundaries of what Large Language Models (LLMs) and Generative AI can achieve.
Join us in building the future of intelligence.
Responsibilities
- Architect Future-Ready AI Systems: Design and deploy scalable machine learning pipelines for Generative AI and Autonomous Agents.
- Optimize LLM Inference: Implement advanced optimization techniques (quantization, pruning, distillation) to ensure low-latency performance in production environments.
- Research & Development: Conduct cutting-edge research in multi-modal AI and reinforcement learning to stay ahead of 2026 tech trends.
- MLOps Implementation: Build robust CI/CD pipelines for model training, testing, and deployment using Kubernetes and cloud-native architectures.
- Ethical AI Governance: Develop frameworks to ensure AI systems are fair, transparent, and safe for global deployment.
- Cross-Functional Collaboration: Partner with product managers and engineering teams to translate complex AI capabilities into user-centric features.
Qualifications
- Advanced Degree: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Core Expertise: Deep proficiency in Python, PyTorch, or TensorFlow with 5+ years of experience in production ML systems.
- LLM Knowledge: Strong understanding of Transformer architectures, RAG (Retrieval-Augmented Generation), and fine-tuning methodologies.
- System Design: Experience designing high-availability distributed systems and microservices architectures.
- Tools & Cloud: Hands-on experience with AWS, GCP, or Azure; familiarity with LangChain, Hugging Face, and MLflow.
- Problem Solving: Proven track record of solving complex algorithmic problems and delivering innovative solutions under tight deadlines.