Job Description
Join the Vanguard of Artificial Intelligence
Are you a visionary engineer ready to shape the future of the 2025 tech landscape? Apex Innovations is seeking a Senior AI Engineer to lead the development of cutting-edge Generative AI models and scalable machine learning infrastructure. In this pivotal role, you will bridge the gap between theoretical research and production-grade applications, driving innovation that impacts millions.
We offer a competitive compensation package, equity options, and the opportunity to work in a dynamic, remote-first culture based in the heart of San Francisco.
Why Join Us?
- Work on next-generation Large Language Models (LLMs).
- Competitive salary: $180k - $260k + Equity.
- Comprehensive health, dental, and vision coverage.
- Flexible remote work options.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art transformer-based models for NLP and computer vision applications.
- System Architecture: Architect robust MLOps pipelines to ensure scalability, reliability, and high-performance inference.
- Research & Innovation: Stay ahead of the curve in AI research, implementing novel techniques to improve model accuracy and efficiency.
- Code Review & Mentorship: Lead code reviews for junior engineers and mentor team members on best practices in AI/ML development.
- Deployment: Deploy models to production environments using Kubernetes and cloud-native services (AWS/GCP).
- Collaboration: Partner with product managers and data scientists to define technical requirements and deliver high-impact features.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field (or equivalent professional experience).
- Experience: 5+ years of professional experience in software engineering or machine learning engineering.
- Programming: Strong proficiency in Python, with deep knowledge of PyTorch or TensorFlow.
- Algorithms: Solid understanding of data structures, algorithms, and mathematical foundations of machine learning.
- Tools: Experience with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).
- Communication: Excellent verbal and written communication skills, capable of translating complex technical concepts for diverse audiences.