Job Description
Are you ready to architect the intelligence of tomorrow? Nexus AI Labs is seeking a visionary Generative AI Engineer to lead our next wave of innovation. We are building the future of synthetic data and autonomous agents, and we need a technical expert to define the roadmap for our core generative models. If you are passionate about pushing the boundaries of what's possible with Large Language Models (LLMs) and multimodal systems, this is your opportunity to shape the industry standard for 2026.
Why Join Us?
- Cutting-Edge Tech Stack: Work with the latest in PyTorch, TensorFlow, and proprietary transformer architectures.
- Impactful Work: Your models will power the next generation of enterprise automation tools used by Fortune 500 companies.
- Equity & Benefits: Competitive compensation package with full health coverage, remote-first flexibility, and significant equity options.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art Generative AI models, focusing on LLMs and diffusion models for text and image generation.
- Optimization: Implement inference optimizations, quantization techniques, and efficient training pipelines to reduce latency and cost.
- Research & Deployment: Bridge the gap between research and production by deploying scalable MLOps solutions on cloud infrastructure (AWS/GCP).
- System Design: Architect robust systems for Retrieval-Augmented Generation (RAG) and autonomous agent workflows.
- Collaboration: Partner with product managers and data scientists to define technical requirements and roadmap features.
- Code Quality: Maintain high standards of code quality, documentation, and testing within an agile environment.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering, with specific expertise in deep learning frameworks.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; strong understanding of Transformer architectures (BERT, GPT, ViT).
- Tools: Experience with MLOps tools (MLflow, Kubeflow) and cloud services (AWS SageMaker, GCP Vertex AI).
- Problem Solving: Demonstrated ability to debug complex distributed systems and optimize performance bottlenecks.
- Communication: Excellent verbal and written communication skills, capable of translating technical concepts for diverse stakeholders.