Job Description
Are you ready to shape the future of artificial intelligence? NeuralPath Systems is seeking a world-class Senior Machine Learning Engineer to join our elite R&D team in San Francisco. We are building the next generation of generative AI and predictive analytics platforms that power enterprise solutions globally.
In this role, you will bridge the gap between theoretical research and production-grade software engineering. You will work directly with Principal Investigators and Data Scientists to engineer scalable models that handle billions of data points in real-time.
Responsibilities
- Model Architecture & Development: Design, implement, and optimize complex deep learning models (CNNs, RNNs, Transformers) using Python and modern frameworks like PyTorch and TensorFlow.
- Data Pipeline Engineering: Build robust, automated data preprocessing pipelines to ensure high-quality training datasets for model training.
- MLOps Deployment: Oversee the end-to-end machine learning lifecycle, from experimentation to deployment in cloud environments (AWS/Azure/GCP).
- Performance Optimization: Profiler and optimize model inference latency and resource utilization to ensure scalability under high load.
- Collaboration: Partner with cross-functional teams including Data Scientists, Product Managers, and Software Engineers to integrate AI capabilities into consumer-facing products.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering, with a proven track record of shipping production models.
- Technical Skills: Deep proficiency in Python, Scikit-learn, PyTorch, and SQL.
- Domain Knowledge: Strong understanding of NLP or Computer Vision is highly preferred.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.