Job Description
Welcome to Nexus Future Labs, where we are architecting the next generation of artificial intelligence. We are seeking a visionary Senior AI Engineer to lead our research and development initiatives in Large Language Models (LLMs) and Generative AI. If you are passionate about pushing the boundaries of machine learning and solving complex problems at scale, we want to meet you.
In this role, you will collaborate with world-class researchers and engineers to build state-of-the-art AI systems that redefine human-computer interaction. You will be responsible for designing scalable architectures, optimizing model performance, and deploying robust solutions to production environments.
Why Join Us?
We offer a competitive compensation package, equity, and the opportunity to work on groundbreaking projects that impact millions of users worldwide. Our culture is built on innovation, transparency, and a relentless pursuit of excellence.
Responsibilities
- Design & Develop: Architect and implement scalable AI/ML solutions, specifically focusing on LLM fine-tuning, RAG pipelines, and generative text models.
- Model Optimization: Apply techniques such as quantization, pruning, and distillation to optimize model inference speed and reduce latency.
- Research: Stay at the forefront of AI research by exploring novel architectures and contributing to open-source communities.
- Production Deployment: Manage the full lifecycle of models from research to deployment, ensuring high availability and reliability using cloud infrastructure (AWS/GCP).
- Collaboration: Partner with product and engineering teams to translate complex technical requirements into actionable AI features.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically in AI/ML model development.
- Programming: Proficiency in Python and deep understanding of PyTorch or TensorFlow.
- LLM Expertise: Proven experience working with LLMs (e.g., GPT-4, LLaMA, Claude), fine-tuning strategies, and prompt engineering.
- Infrastructure: Experience with cloud platforms (AWS/GCP) and containerization tools (Docker, Kubernetes).
- Problem Solving: Strong analytical skills with the ability to debug complex distributed systems and optimize algorithms.