Job Description
Architecting the Intelligence of Tomorrow
We are a venture-backed startup pioneering the next wave of Autonomous AI Agents. As we move toward our 2026 Roadmap, we are seeking a visionary Senior Generative AI Engineer to lead the development of proprietary Large Language Models (LLMs) and multi-modal systems. You will work at the intersection of deep learning research and scalable production engineering.
Why Join Us?
- Work on cutting-edge GenAI technology that will define the industry standards for 2026.
- Competitive equity package and a flexible, remote-first culture.
- Access to the latest hardware and research libraries.
If you are passionate about pushing the boundaries of what AI can achieve, we want to hear from you.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art LLMs (e.g., GPT-4, Llama 3) for specific enterprise applications.
- RAG Pipelines: Build robust Retrieval-Augmented Generation architectures to enhance model accuracy and reduce hallucinations.
- Optimization: Optimize model inference latency and throughput using techniques like quantization and distillation.
- Agent Orchestration: Integrate AI models into autonomous agent workflows and manage context windows dynamically.
- Research: Stay ahead of the curve by implementing novel architectures and papers from top-tier conferences (NeurIPS, ICML).
- Code Review: Mentor junior engineers and enforce best practices for AI deployment and MLOps.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in Python, with at least 2 years focused on Machine Learning or Deep Learning.
- Technical Skills: Proficiency in PyTorch or TensorFlow; experience with Hugging Face Transformers and LangChain.
- Mathematics: Strong understanding of linear algebra, calculus, and probability theory.
- Communication: Ability to translate complex technical concepts into clear, actionable insights for stakeholders.
- Agile Mindset: Experience working in fast-paced, agile environments.