Artificial Intelligence Engineer in San Francisco | Architect the Intelligence of Tomorrow

Join a pioneering team where your code doesn’t just run—it thinks, learns, and transforms the world. We are not looking for a mere practitioner; we need an AI architect who can translate the most complex theoretical breakthroughs into robust, high-impact production systems that serve millions. This is a rare opportunity to shape the foundational intelligence layer for products used globally.

About the Role

You will be a core member of our Advanced AI Lab, moving beyond prototypes to own the full lifecycle of intelligent systems. Your work will directly influence our core product roadmap, tackling challenges in natural language understanding, computer vision, and large-scale predictive modeling. You will research, experiment, and then industrialize models, ensuring they are efficient, fair, and scalable in real-world environments.

Key Responsibilities

• Design, train, and optimize deep learning models (LLMs, diffusion models, etc.) for diverse product applications.
• Build and maintain scalable data pipelines and MLOps infrastructure for continuous model training and deployment.
• Collaborate cross-functionally with product, research, and infrastructure teams to define AI strategy and feasibility.
• Pioneer novel approaches to unsolved problems, publishing internally and contributing to the broader AI community.
• Ensure model performance, scalability, and ethical integrity through rigorous testing and monitoring.

What You Bring (Requirements)

We value depth over checklist perfection. You are a builder who thrives on intellectual rigor and tangible outcomes.

Essential Expertise

• 5+ years of hands-on experience in machine learning engineering or applied AI research roles.
• Mastery of Python and major ML frameworks (PyTorch, TensorFlow, JAX).
• Proven track record of deploying complex ML models into production at scale.
• Deep understanding of core ML/DL concepts, from transformer architectures to optimization theory.
• Experience with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes).

Preferred Distinctions

• PhD in Computer Science, Machine Learning, or a related quantitative field.
• Experience with large-scale distributed training and inference optimization.
• Contributions to open-source ML projects or publications at top-tier conferences (NeurIPS, ICML, CVPR).
• Familiarity with reinforcement learning or multi-modal AI systems.

Compensation & Benefits

We believe in exceptional compensation for exceptional talent. This is a senior-level role with total compensation reflective of San Francisco’s market and the immense value you will create.

Salary Range

$150,000 – $220,000 USD/year (base salary) + Significant Equity Package + Annual Performance Bonus.

*Final offer will be based on experience, expertise, and market rate.

Comprehensive Benefits Suite

• Health & Wellness: 100% premium coverage for you and dependents (medical, dental, vision), mental health stipend.
• Financial Security: 401(k) match, generous equity grants, student loan repayment assistance.
• Time Off: Flexible PTO policy, sabbatical opportunities after 5 years, paid parental leave.
• Growth: $5,000 annual learning & development budget, conference travel, dedicated time for research.
• Perks: Home office stipend, commuter benefits, gourmet meals, wellness programs.

The Culture & Mission

You will join a mission-driven organization that believes intelligence is the most powerful tool for positive human progress. We foster a culture of “intellectual humility and bold ambition”—where debate is encouraged, failure is a data point, and breakthroughs are celebrated. We are an all-remote-friendly team with a hub in San Francisco, built on trust, transparency, and a shared obsession with building technology that matters.

If you are ready to move beyond incremental improvements and tackle problems that require genuine creativity and deep technical prowess, we want to hear from you. Help us build the intelligent systems that will power the next decade.