Job Description
Are you ready to architect the intelligent systems of tomorrow? Nebula Systems is seeking a visionary Senior AI Engineer to lead our next-generation artificial intelligence initiatives. We are not just building models; we are defining the future of human-machine interaction in the United States.
In this pivotal role, you will spearhead the development of scalable machine learning infrastructure, optimize neural networks for real-time processing, and mentor a team of high-potential engineers. If you thrive in a fast-paced, innovative environment and want to solve complex problems that shape the industry, we want to meet you.
Why Join Nebula Systems?
- Work with cutting-edge technologies including Large Language Models and Generative AI.
- Competitive salary package with comprehensive health benefits and equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Opportunity to publish research and speak at global tech conferences.
Responsibilities
- Design, develop, and deploy advanced machine learning models and algorithms to solve complex business problems.
- Lead the full software development lifecycle (SDLC) for AI products, from data ingestion to model deployment.
- Collaborate with cross-functional teams (Product, Data Science, and Engineering) to translate business requirements into technical solutions.
- Optimize existing models for speed, accuracy, and scalability in high-volume production environments.
- Conduct code reviews and provide technical mentorship to junior engineers and data scientists.
- Stay abreast of the latest advancements in AI research and integrate relevant innovations into our architecture.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- 5+ years of professional experience in building and deploying production-level AI/ML models.
- Strong proficiency in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Deep understanding of statistical analysis and data mining techniques.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.