Job Description
Are you ready to architect the future of intelligent systems? Nebula Dynamics is seeking a visionary Senior AI/ML Engineer to lead our research and development initiatives for the 2026 technology roadmap.
We are not just building software; we are defining the next era of human-machine interaction. In this role, you will spearhead the deployment of scalable deep learning models, optimize real-time inference pipelines, and mentor a team of top-tier data scientists. If you are passionate about pushing the boundaries of Generative AI and Large Language Models (LLMs), we want to hear from you.
Why Join Us?
- Impactful Work: Build systems that will power the infrastructure of tomorrow.
- Top-Tier Compensation: Competitive salary plus equity package.
- Innovation Culture: Work in a state-of-the-art facility with access to the latest hardware.
Join us in San Francisco and be at the forefront of the AI revolution.
Responsibilities
- Lead Model Development: Design, train, and deploy advanced machine learning models, with a focus on Generative AI and Natural Language Processing.
- System Optimization: Architect high-performance inference pipelines capable of handling millions of requests per second with sub-millisecond latency.
- R&D Leadership: Conduct cutting-edge research to explore new architectures and algorithms relevant to the 2026 technological landscape.
- Production Engineering: Collaborate with DevOps teams to ensure robust, scalable, and secure deployment of ML models in cloud environments (AWS/GCP).
- Mentorship: Guide and mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: Minimum of 5+ years of professional experience in AI/ML engineering, with a proven track record of deploying production-ready models.
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow. Deep understanding of Deep Learning architectures (Transformers, GANs, RNNs).
- Infrastructure: Strong experience with distributed computing frameworks (Kubernetes, Docker) and cloud services (AWS SageMaker, Google AI Platform).
- Communication: Excellent written and verbal communication skills, with the ability to translate complex technical concepts for diverse stakeholders.