Job Description
Are you ready to architect the intelligence of tomorrow?
Nexus Future Labs is seeking a visionary Senior AI Engineer to lead the development of next-generation Generative AI systems. As we prepare for the technological landscape of 2026, we need an expert who can bridge the gap between cutting-edge research and scalable production engineering.
In this role, you will spearhead the design and deployment of Large Language Models (LLMs) and Autonomous Agents, directly shaping how humans interact with AI in the enterprise sector. You will work in a high-impact environment where your code defines the future.
Why Join Us?
- Work on projects that redefine industry standards.
- Competitive compensation and equity package.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale generative models using transformer architectures and reinforcement learning from human feedback (RLHF).
- System Architecture: Build robust, scalable pipelines for data processing, model training, and inference serving.
- RAG Implementation: Develop and optimize Retrieval-Augmented Generation systems to ensure accuracy and reduce hallucinations.
- Performance Optimization: Engineer high-throughput, low-latency inference engines for real-time AI applications.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate business requirements into technical AI solutions.
- Mentorship: Guide junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years focused on Generative AI or Deep Learning.
- Programming: Proficiency in Python, PyTorch, or TensorFlow; experience with C++ for performance optimization is a plus.
- Tools: Strong understanding of MLOps tools (MLflow, Kubeflow), containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, or Azure).
- Mathematics: Solid foundation in linear algebra, calculus, and probability statistics.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.