Job Description
At Nexus AI Systems, we are building the next generation of autonomous infrastructure. We are seeking a visionary Senior Machine Learning Engineer to join our core research team in San Francisco. You will be responsible for scaling our generative models and optimizing neural network inference for real-time industrial applications.
This is a high-impact role where your work will directly influence the scalability of our proprietary AI platform. We provide an environment that fosters technical excellence, rapid experimentation, and intellectual freedom.
Responsibilities
- Design, implement, and deploy production-grade machine learning models to solve complex pattern recognition tasks.
- Optimize model training pipelines using distributed computing frameworks for high-throughput data processing.
- Collaborate with cross-functional teams to integrate ML solutions into cloud-native microservices.
- Conduct cutting-edge research to improve model accuracy, latency, and resource efficiency.
- Mentor junior engineers and champion best practices in ML observability and CI/CD for AI.
- Maintain technical documentation and present research findings to stakeholders and technical leadership.
Qualifications
- M.S. or Ph.D. in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in deep learning, computer vision, or natural language processing.
- Expert-level proficiency in Python and industry-standard frameworks such as PyTorch or TensorFlow.
- Deep understanding of distributed training techniques and model optimization (quantization, pruning).
- Proven track record of deploying scalable ML models in cloud environments like AWS or GCP.
- Experience with data orchestration tools and MLOps lifecycle management (Kubeflow, MLflow).
- Strong analytical mindset and ability to translate ambiguous business requirements into technical roadmaps.