Job Description
Are you ready to shape the future of artificial intelligence? Nexus Innovations is seeking a visionary Senior AI & Machine Learning Engineer to join our elite engineering team in San Francisco. In this pivotal role, you will be responsible for designing, deploying, and optimizing scalable machine learning systems that drive our core product strategy.
We are looking for a thought leader who thrives in a fast-paced environment and is passionate about pushing the boundaries of what's possible with data. If you have a deep understanding of neural networks and a knack for translating complex algorithms into user-centric solutions, we want to hear from you.
Why Join Us?
- Competitive compensation and equity package.
- Access to cutting-edge hardware and cloud resources.
- Collaborative culture with top-tier talent from the industry's leading tech giants.
Responsibilities
- Architect and implement end-to-end machine learning pipelines and production-grade models.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements and deliver high-quality software.
- Research and evaluate new machine learning algorithms and techniques to stay ahead of industry trends.
- Mentor junior engineers and conduct code reviews to ensure best practices in software engineering and data science.
- Optimize models for latency, throughput, and scalability to support high-traffic applications.
Qualifications
- Master's or PhD degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Minimum of 5+ years of professional experience in machine learning and software engineering.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep experience with distributed computing frameworks (e.g., Apache Spark, Kubernetes) and cloud platforms (AWS/GCP/Azure).
- Proven track record of deploying models to production environments with high availability.
- Excellent problem-solving skills and ability to work independently in a remote-first hybrid setting.