Job Description
Shape the Future of Intelligence
Nexus Future Labs is pioneering the technological landscape of 2026. We are looking for a visionary Senior AI Engineer to architect and deploy next-generation Agentic AI systems. In this role, you will build the core infrastructure that powers autonomous decision-making and advanced natural language processing, defining how humans interact with machines in the coming decade.
Why Nexus Future Labs?
- Impactful Work: Engineer systems that will define the AI standard for 2026 and beyond.
- Top-Tier Compensation: Competitive salary and equity package.
- Flexible Environment: Hybrid work model with a focus on autonomy and results.
Join us in building the intelligent systems of tomorrow.
Responsibilities
- Architect Scalable AI Infrastructure: Design and maintain robust machine learning pipelines capable of handling petabyte-scale data for 2026-scale applications.
- Develop Agentic Systems: Build autonomous AI agents that can plan, execute, and learn from complex tasks without human intervention.
- Model Optimization: Fine-tune large language models (LLMs) and optimize inference speeds for edge and cloud deployment.
- Research & Innovation: Stay at the forefront of AI research, implementing novel techniques in reinforcement learning and transformer architectures.
- Cross-Functional Collaboration: Partner with product managers and engineers to translate complex AI capabilities into user-friendly products.
- Rigorous Validation: Implement testing frameworks to ensure model safety, accuracy, and bias mitigation.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a focus on NLP or Generative AI.
- Technical Stack: Deep proficiency in Python, PyTorch, or TensorFlow.
- LLM Expertise: Proven experience working with Large Language Models (e.g., GPT, Llama, Claude) including fine-tuning and RAG pipelines.
- Infrastructure: Strong understanding of cloud computing (AWS/GCP) and containerization (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems in a dynamic environment.