Applied AI ML-Vice President

Job Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
• Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
• Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
• Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
• Promote software and model quality, integrity, and security across the organization

Required Qualifications, Capabilities, And Skills

• BS in Computer science or similar fields with 5+ years experience or MS in Computer science or similar fields with 3+ years experience, with training and work experience in LLM/NLP and search.
• Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
• Experience in machine learning frameworks, ML Ops tools and practices
• Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
• Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD)

Preferred Qualifications, Capabilities, And Skills

• Optional, great to have - experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems).