Job Description
Shape the Future of Intelligence
Welcome to Nexus Future Labs, where we are architecting the next generation of Artificial Intelligence. We are seeking a visionary Senior AI/ML Engineer to spearhead the development of autonomous systems and next-gen neural networks. If you are passionate about pushing the boundaries of what is possible in machine learning and want to define the trajectory of AI for 2026 and beyond, we want to hear from you.
In this role, you will not just write code; you will build the cognitive infrastructure of tomorrow. You will work in a high-performance environment, collaborating with world-class researchers and engineers to solve complex problems in Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning.
Why Join Us?
- Competitive compensation and equity package.
- Flexible remote-first policy with a San Francisco hub.
- Access to cutting-edge hardware and research libraries.
Responsibilities
- Model Architecture: Design, implement, and optimize state-of-the-art machine learning models and deep learning algorithms.
- Research & Development: Conduct rigorous research to improve model accuracy, efficiency, and scalability for production environments.
- Infrastructure: Build and maintain robust MLOps pipelines, ensuring seamless deployment and monitoring of models in the cloud.
- Collaboration: Partner with product managers and data scientists to translate business requirements into technical AI solutions.
- Code Quality: Write clean, maintainable, and well-documented code; mentor junior engineers and conduct technical code reviews.
- Ethics & Safety: Ensure AI models adhere to ethical guidelines and safety standards to prevent bias and ensure fairness.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Programming: Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience: 5+ years of experience in machine learning engineering or applied research.
- Specialization: Deep experience with NLP, LLMs, or Computer Vision is highly preferred.
- Cloud Skills: Proven track record of deploying models on cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Ability to troubleshoot complex issues and optimize model inference latency.