Job Description
Are you ready to redefine the future of artificial intelligence?
Nexus AI Systems is on the lookout for a visionary Senior AI Engineer to join our elite R&D team in San Francisco. We are building the next generation of autonomous machine learning systems that will power enterprise solutions globally. If you have a deep passion for algorithms, data architecture, and scalable machine learning models, we want to hear from you.
As a Senior AI Engineer at Nexus, you won't just be writing code; you will be architecting the intelligence behind our flagship products. You will collaborate with world-class researchers and product managers to transform complex datasets into actionable, predictive models.
Why Join Us?
- Impact: Work on projects that have a direct impact on millions of users worldwide.
- Innovation: Access to cutting-edge hardware and the freedom to experiment with the latest AI frameworks.
- Growth: Comprehensive benefits, equity packages, and continuous learning opportunities.
We are committed to an inclusive environment and welcome candidates from all backgrounds.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and deep learning architectures.
- Lead the end-to-end data pipeline lifecycle, from data ingestion and cleaning to model training and evaluation.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define AI requirements and deliver scalable solutions.
- Mentor junior engineers and provide technical guidance on best practices in MLOps and model deployment.
- Optimize existing models for latency, throughput, and accuracy to ensure high performance in production environments.
- Stay current with the latest research in AI/ML and evaluate new technologies for integration into our stack.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
- 5+ years of professional experience in machine learning, deep learning, or AI research.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience with big data technologies (Spark, Hadoop, or cloud data warehouses).
- Experience with MLOps tools and cloud platforms (AWS, GCP, or Azure).
- Proven track record of deploying production-ready models and managing model lifecycle.
- Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.