Job Description
The Opportunity
Nexus Future Systems is pioneering the next generation of autonomous decision-making algorithms. As part of our elite Project 2026 initiative, you will be at the forefront of developing the foundational models that will power intelligent systems a decade from now. We are looking for a visionary Senior Machine Learning Engineer to lead our R&D efforts in San Francisco.
Why Join Us?
- High-Impact Work: Directly influence the roadmap of the next major technological leap.
- Top-Tier Compensation: Competitive salary plus equity package.
- Modern Stack: Access to cutting-edge compute resources and the latest open-source frameworks.
The Role
You will bridge the gap between theoretical research and scalable production deployment. Working in a fast-paced, collaborative environment, you will design architectures that push the limits of what is currently possible in neural network efficiency and reasoning.
Responsibilities
- Lead the architecture and implementation of core machine learning models for Project 2026.
- Optimize deep learning pipelines for low-latency, high-throughput inference in production environments.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers.
- Experiment with novel training techniques and regularization methods to improve model robustness.
- Establish best practices for model monitoring, evaluation, and explainability.
- Contribute to the technical vision and mentor junior engineers on the team.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning engineering.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Strong background in distributed training, optimization, and large-scale data processing.
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow).
- Proven track record of deploying production-grade models at scale.