Job Description
We are on a mission to redefine the boundaries of artificial intelligence. Nexus AI is seeking a visionary Senior AI/ML Engineer to join our elite engineering team. If you are passionate about building scalable, production-grade machine learning systems and want to work on problems that matter, we want to meet you.
In this role, you will bridge the gap between cutting-edge research and real-world application. You will own the architecture of our core models, optimize inference pipelines, and collaborate with cross-functional teams to deliver solutions that drive our business forward.
Why join us?
- Competitive compensation and equity package.
- Flexible work environment with remote-first options.
- Access to the latest hardware and cloud infrastructure.
- Opportunities for professional growth and leadership.
Responsibilities
- Design, develop, and deploy robust machine learning models and algorithms for large-scale data processing.
- Build and maintain high-performance data pipelines and infrastructure using cloud-native technologies.
- Collaborate with data scientists and product managers to translate business requirements into technical solutions.
- Mentor junior engineers and conduct code reviews to ensure best practices in software architecture.
- Continuously monitor model performance and implement strategies for A/B testing and model drift detection.
- Stay abreast of the latest research in deep learning and NLP/CV to integrate innovative techniques into our stack.
Qualifications
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning engineering or data science.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience with distributed computing frameworks (e.g., Apache Spark, Dask) and cloud platforms (AWS, GCP, or Azure).
- Deep understanding of MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.