Job Description
We are at the forefront of the artificial intelligence revolution. Nexus Future Labs is building the operating system for next-generation AI applications. We are seeking a visionary Senior AI Engineer & LLM Specialist to join our elite team in San Francisco. You will be instrumental in architecting, training, and deploying state-of-the-art Large Language Models (LLMs) that will power the future of enterprise intelligence.
In this role, you will bridge the gap between cutting-edge research and production-grade software engineering. You will work with a diverse team of data scientists, researchers, and product engineers to solve complex problems in natural language processing (NLP), machine learning operations (MLOps), and generative AI.
Why Join Us?
- Impactful Work: Your code will directly influence how millions of users interact with AI.
- Road to 2026: We are pioneering the roadmap for AGI (Artificial General Intelligence) development.
- Competitive Package: Top-tier salary, equity, and comprehensive benefits.
- Flexible Culture: Hybrid work model with a focus on autonomy and innovation.
Responsibilities
- Model Architecture & Development: Design and implement scalable architecture for training, fine-tuning, and serving large-scale foundation models using PyTorch and TensorFlow.
- RAG Pipeline Optimization: Build and optimize Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and reduce hallucinations.
- Performance Engineering: Proficiently tune model inference latency and throughput to meet real-time production SLAs.
- MLOps Implementation: Design and manage CI/CD pipelines for machine learning using tools like MLflow, Airflow, and Kubernetes to automate model deployment and monitoring.
- Research Integration: Stay abreast of the latest academic research in transformer architectures and deep learning to integrate novel techniques into our production stack.
- Code Review & Mentorship: Conduct rigorous code reviews and mentor junior engineers and data scientists on best practices for AI engineering.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (or equivalent practical experience).
- Technical Skills: Strong proficiency in Python, PyTorch, and TensorFlow; deep understanding of Hugging Face Transformers and ecosystem.
- Experience: 5+ years of experience in software engineering with a focus on machine learning or AI.
- LLM Expertise: Proven experience in fine-tuning LLMs (e.g., Llama, GPT, Claude) and deploying them via APIs (vLLM, TGI, Sagemaker).
- System Design: Experience designing distributed systems capable of handling high concurrency and large-scale data processing.
- Soft Skills: Excellent problem-solving abilities, strong communication skills, and a passion for the future of AI.