Job Description
We are looking for a visionary Senior AI/ML Engineer to architect the next generation of intelligent systems at Nexus Horizon. In this role, you will bridge the gap between theoretical machine learning and scalable production infrastructure, working on cutting-edge generative AI and large language model (LLM) applications. If you are passionate about solving complex problems and pushing the boundaries of what's possible in AI, we want to hear from you.
Why Join Nexus Horizon?
- Work with state-of-the-art technologies including PyTorch, TensorFlow, and modern MLOps tools.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with a hub in San Francisco.
- Collaborative environment with industry leaders in deep learning.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale machine learning models to optimize for accuracy, latency, and resource efficiency.
- Infrastructure & MLOps: Build and maintain robust CI/CD pipelines and deployment infrastructure using Kubernetes and cloud platforms (AWS/GCP).
- System Architecture: Lead the architectural design of data ingestion pipelines and model serving frameworks to ensure high availability and scalability.
- Code Review & Mentorship: Provide technical leadership, conduct rigorous code reviews, and mentor junior engineers and data scientists on best practices.
- Performance Optimization: Continuously monitor model performance in production, identifying bottlenecks and implementing optimizations to reduce inference costs.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 5+ years of professional experience in machine learning engineering, with a strong focus on NLP or Computer Vision.
- Programming: Expert proficiency in Python and experience with deep learning frameworks (PyTorch or TensorFlow).
- MLOps: Deep understanding of MLOps practices, containerization (Docker), and orchestration (Kubernetes).
- Problem Solving: Proven track record of delivering high-impact ML products in a fast-paced, agile environment.