Job Description
Are you ready to architect the intelligence of tomorrow? 2026 is at the forefront of next-generation generative AI, building the foundational models that will redefine human-machine interaction. We are seeking a visionary Senior AI/ML Engineer to join our elite engineering team in San Francisco.
In this role, you won't just be maintaining systems; you will be building the future. We are looking for a technical leader who thrives in ambiguity and possesses a deep understanding of deep learning architectures, scalable inference pipelines, and the ethical implications of AI deployment.
Why join 2026?
- Work on cutting-edge Large Language Models (LLMs) and Autonomous Agents.
- Competitive equity package and top-tier compensation.
- Remote-first culture with a hub in the heart of SF.
If you are passionate about pushing the boundaries of what is possible with artificial intelligence, we want to hear from you.
Responsibilities
- Design, train, and deploy scalable machine learning models and neural networks.
- Optimize inference latency and throughput for high-volume production environments.
- Collaborate with cross-functional teams of data scientists, product managers, and researchers to define AI product requirements.
- Research and implement novel techniques in NLP, Computer Vision, or Reinforcement Learning.
- Mentor junior engineers and establish best practices for code quality and model governance.
- Monitor model performance, conduct A/B testing, and iterate rapidly based on user feedback.
Qualifications
- PhD or Master’s degree in Computer Science, Statistics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in machine learning, deep learning, or data science.
- Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of shipping production-ready AI applications.
- Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.