About the Role
Lead the design and implementation of advanced AI models and infrastructure, driving technical strategy and mentoring engineering teams to achieve high-impact outcomes in a fast-paced environment.
Responsibilities
- Define technical direction for AI initiatives across multiple product teams
- Develop and optimize large-scale machine learning systems
- Mentor engineers and data scientists in best practices for AI development
- Collaborate with product and research teams to identify AI opportunities
- Design robust data pipelines to support model training and inference
- Evaluate and integrate emerging AI frameworks and tools
- Ensure models meet performance, scalability, and reliability standards
- Drive innovation in natural language processing and computer vision
- Lead code reviews and architectural discussions for AI components
- Improve model monitoring, versioning, and deployment workflows
- Contribute to ethical AI practices and bias mitigation strategies
- Publish research findings and represent the organization at conferences
- Troubleshoot complex system-level issues in production environments
- Establish standards for experiment tracking and reproducibility
- Guide selection of hardware and infrastructure for AI workloads
- Support integration of AI capabilities into customer-facing products
- Promote knowledge sharing through internal talks and documentation
- Evaluate third-party AI services and open-source contributions
- Ensure compliance with data privacy and security requirements
- Collaborate on long-term roadmap planning for AI platform evolution
Nice to Have
- PhD in machine learning, artificial intelligence, or related discipline
- Leadership experience in AI research or engineering teams
- Publications in top-tier AI conferences or journals
- Hands-on experience with reinforcement learning techniques
- Expertise in model quantization, pruning, or on-device inference
- Experience scaling AI systems to millions of users
- Contributions to major open-source machine learning libraries
- Background in high-performance computing or GPU optimization
- Familiarity with formal verification methods for AI systems
- Experience with multimodal AI systems combining text, image, and audio
Compensation
Competitive salary with equity and performance bonuses
Work Arrangement
Hybrid work model with flexible remote options
Team
Collaborative team of machine learning experts and software engineers
About the Team
Work within a dedicated AI group that bridges research and product development, focusing on real-world deployment of cutting-edge models.
Technology Stack
Primary tools include Python, PyTorch, Kubernetes, AWS, Docker, and custom training frameworks for large-scale model development.
Available for qualified candidates
