Role overview
The Director of Machine Learning is a senior leadership role responsible for shaping, executing, and scaling the organization’s machine learning strategy. This leader oversees the development and deployment of advanced ML models, guides cross-functional teams, and ensures the organization leverages AI technologies to drive innovation, efficiency, and business impact. The ideal candidate has deep technical expertise, proven leadership experience, and the ability to translate complex ML concepts into meaningful business outcomes.
What you'll work on
Strategic Leadership
- Develop and own the company-wide machine learning strategy aligned with business objectives
- Identify high-impact opportunities for ML across products, operations, and customer experiences
- Advocate for ethical, secure, and responsible AI development and usage
Team & Project Management
- Lead, mentor, and grow high-performing teams of ML engineers, data scientists, and research scientists
- Establish best practices in model development, experimentation, deployment, and monitoring
- Allocate team resources and prioritize projects to balance innovation with ROI
Technical Leadership
- Oversee the design, development, and deployment of production-grade machine learning models
- Partner with engineering leadership to build scalable ML infrastructure, including MLOps, data pipelines, and cloud architecture
- Review and guide technical work, ensuring scientific rigor, reproducibility, and quality
Cross‑Functional Collaboration
- Work closely with product, engineering, data, and executive teams to align ML initiatives with organizational goals
- Communicate complex ML concepts—tradeoffs, risks, timelines—to non-technical stakeholders
- Support product strategy by integrating ML capabilities into roadmaps
Governance & Performance
- Implement processes for model governance, bias monitoring, versioning, and auditability
- Track and report on key ML KPIs, model performance, and business impact
- Ensure compliance with regulatory standards related to AI/ML as applicable
What we're looking for
Required
- Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or related field
- 10+ years of experience in ML/AI engineering, data science, or applied research
- 5+ years leading technical teams, including people management responsibility
- Expertise in modern ML techniques (deep learning, LLMs, reinforcement learning, generative models, etc.)
- Proficiency with ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face)
- Strong understanding of MLOps, cloud platforms (Azure, AWS, GCP), and scalable data architectures
- Proven track record deploying ML models into production environments
- Experience building ML platforms or ML-driven products at scale
- Background working in regulated industries (finance, healthcare, etc.) if relevant
- Demonstrated experience with LLM fine-tuning, retrieval-augmented generation (RAG), or generative AI
- Strong business acumen and ability to influence senior leaders
Key Competencies
- Strategic thinking and vision‑setting
- Excellent communication and stakeholder management
- Technical depth paired with practical delivery
- Leadership, coaching, and talent development
- Innovation mindset with data‑driven decision-making
The targeted pay range for this position in the following location is / locations are:
United States - Redwood City Office GHQ : 240,000 - 360,000 USD / Annual
Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.
The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.