Job Description
Are you ready to shape the future of Artificial Intelligence? NeuralNet Solutions is seeking a world-class Senior Machine Learning Engineer to join our elite team in the heart of San Francisco. We are on a mission to deploy AI solutions that drive real-world impact, and we need a technical visionary to lead our engineering efforts.
In this role, you won't just write code; you will architect the neural pathways of our next-generation products. You will work alongside top-tier data scientists and engineers in a dynamic, fast-paced environment, pushing the boundaries of what's possible in NLP and Computer Vision.
We offer a competitive compensation package including equity, comprehensive health benefits, and a flexible remote-first policy with a stipend for home office setup.
Responsibilities
- Model Development: Design, train, and optimize complex machine learning models using state-of-the-art frameworks such as PyTorch and TensorFlow.
- Production Deployment: Lead the end-to-end deployment of ML models into production environments using Docker and Kubernetes.
- System Architecture: Collaborate with system architects to design scalable, fault-tolerant data pipelines and infrastructure.
- Performance Tuning: Continuously monitor model performance, identify bottlenecks, and implement optimizations to ensure high throughput and low latency.
- Research & Innovation: Stay at the forefront of AI research, evaluating new libraries and techniques to integrate into our product stack.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: Minimum of 5+ years of experience in Machine Learning Engineering or Data Science roles.
- Programming: Strong proficiency in Python, C++, or Java.
- Frameworks: Deep experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and MLOps tools (MLflow, Kubeflow).
- Cloud: Experience deploying models on AWS, GCP, or Azure.