Job Description
Are you ready to build the future of technology? Nexus Future Labs is seeking a visionary Senior AI Engineer to join our elite team in San Francisco. We are not just predicting the trends of tomorrow; we are defining them. In this role, you will lead the development of next-generation artificial intelligence systems designed to revolutionize industries by 2026 and beyond.
As a pioneer in the field, you will work at the intersection of data science, deep learning, and scalable infrastructure. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs), Computer Vision, and Generative AI, we want to hear from you.
Why join us?
• Competitive compensation package (Base + Equity)
• Top-tier healthcare and wellness benefits
• Flexible remote-first culture with quarterly in-person meetups
• Access to cutting-edge hardware and cloud resources
Responsibilities
- Architect and Deploy: Design, train, and deploy state-of-the-art machine learning models and neural networks for production environments, ensuring high scalability and low latency.
- Research & Development: Conduct advanced research to pioneer new algorithms and techniques that address complex, real-world business challenges.
- Model Optimization: Fine-tune pre-trained models (e.g., GPT-4, LLaMA) to improve performance, reduce computational costs, and enhance accuracy.
- Collaboration: Partner with cross-functional teams of product managers, engineers, and designers to translate technical requirements into innovative solutions.
- Data Strategy: Oversee the end-to-end data pipeline, ensuring data quality, integrity, and privacy compliance.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in AI, Machine Learning, or Deep Learning.
- Programming: Strong proficiency in Python, with extensive experience using frameworks such as PyTorch, TensorFlow, or JAX.
- Tools: Deep understanding of MLOps tools (e.g., MLflow, Kubeflow, DVC) and cloud platforms (AWS, GCP, or Azure).
- Mathematics: Solid grounding in linear algebra, calculus, probability, and statistics.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.