Job Description
Shape the Future with 2026 Innovations
We are seeking a visionary Senior AI Strategist to join our elite team in San Francisco. At 2026, we are not just predicting the future; we are architecting it. We are building the next generation of adaptive intelligence systems that will redefine human-machine collaboration. If you possess a deep understanding of machine learning lifecycles and a knack for translating complex technical concepts into business value, we want to hear from you.
Why Join Us?
- Impactful Work: Your strategies will directly influence global tech standards.
- Top-Tier Talent: Collaborate with PhDs and industry veterans.
- Competitive Compensation: Salary range of $160k - $220k plus equity.
- Flexible Culture: Hybrid work model supporting work-life balance.
Responsibilities
- Define and execute the long-term AI product roadmap for 2026, aligning technical capabilities with business objectives.
- Lead cross-functional teams in the design, development, and deployment of advanced machine learning models.
- Conduct rigorous market research to identify emerging AI trends and competitive advantages.
- Establish best practices for data governance, ethical AI usage, and model interpretability.
- Present complex technical strategies to C-suite executives and key stakeholders with clarity and conviction.
- Mentor junior strategists and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (PhD preferred).
- Minimum of 7 years of experience in AI strategy, product management, or technical consulting.
- Proven track record of launching successful AI-driven products or initiatives in a fast-paced environment.
- Deep technical fluency in Python, TensorFlow, PyTorch, or similar frameworks.
- Excellent verbal and written communication skills, with the ability to bridge the gap between engineers and business leaders.
- Strong understanding of cloud architecture (AWS, GCP, or Azure) and MLOps pipelines.