Job Description
Are you ready to define the future of Artificial Intelligence?
Nebula AI Solutions is on a mission to pioneer the technological landscape of 2026 and beyond. We are seeking a visionary Senior AI/ML Engineer to join our elite engineering team. If you are passionate about pushing the boundaries of Generative AI, Large Language Models (LLMs), and scalable machine learning architectures, we want to hear from you.
In this role, you won't just maintain systems; you will architect the next generation of intelligent solutions that will define the industry standard for years to come.
Why Join Us?
- Future-Proof Your Career: Work on cutting-edge projects that will shape the trajectory of AI technology through 2026 and beyond.
- Competitive Compensation: Base salary ranging from $180,000 to $250,000, plus equity and performance bonuses.
- Flexible Environment: Hybrid work model based in the heart of San Francisco's tech hub.
We are looking for a technical leader who thrives in ambiguity and possesses a deep understanding of the mathematical foundations of AI.
Responsibilities
- Architect Next-Gen Models: Design and implement scalable AI models and algorithms, specifically focusing on Generative AI and LLM optimization for 2026 deployment standards.
- System Optimization: Oversee the full machine learning lifecycle, from data ingestion and preprocessing to model training, validation, and deployment in production environments.
- Research & Innovation: Stay at the forefront of AI research, experimenting with novel architectures and techniques to improve model accuracy and efficiency.
- Collaborative Leadership: Partner with cross-functional teams of data scientists, software engineers, and product managers to translate complex technical requirements into robust engineering solutions.
- MLOps Implementation: Establish and maintain CI/CD pipelines and MLOps frameworks to ensure seamless model deployment and monitoring.
- Ethical AI Compliance: Ensure all deployed models adhere to ethical guidelines, bias mitigation standards, and regulatory compliance requirements.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.
- Technical Mastery: Extensive experience with Python, PyTorch, TensorFlow, or JAX.
- Modeling Expertise: Deep understanding of Deep Learning, Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Experience: Minimum of 5+ years of professional experience in building and deploying machine learning systems at scale.
- Cloud Proficiency: Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex, ambiguous engineering problems with elegant, scalable solutions.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.