Senior AI/ML Scientist

Responsibilities:

Defines and Oversees Research Strategy 

• Sets the long-term research vision for major projects or entire product areas. 
• Oversees the scientific direction of end-to-end project delivery, ensuring alignment with strategic corporate goals.

Pioneers Breakthrough Innovations

• Moves beyond existing paradigms to invent and develop fundamentally new AI methodologies. 
• Proposes and leads architecture-wide improvements based on emerging scientific insights.

Excels at Scientific Leadership and Mentorship

• Shapes the organization's scientific culture. 
• Excels at coaching other scientists and technical leaders, setting the standard for research practices, and resolving scientific and technical conflicts.

Drives High-Impact Cross-Functional Initiatives

• Regularly leads and influences the most critical, high-impact collaborations between research, product, and engineering. Is accountable for the successful application of research to solve key business challenges.

Acts as a Voice for the Scientific Community

• Represents the company's research interests both internally and externally. 
• Authors and reviews papers for top-tier academic publications, building the company's reputation for innovation.

Demonstrates Deep Business Acumen 

• Possesses an excellent, nuanced understanding of how scientific investments and research directions impact the broader business, influencing product strategy and long-term roadmaps.

Intellectual Property

• Translate complex AI systems into robust, legally defensible claims while ensuring alignment with company IP strategy.

Candidate Profile & Requirements

Profile and Skills

Critical Skills 

Domain Mastery: Recognized as a leading internal expert in a specific AI sub-field, with the ability to contribute to the state of the art.

Invention of Novel Techniques: Proven ability to invent and develop new algorithms, architectures, and methodologies from first principles to solve unique, complex problems.

AI System & Architectural Design: The ability to design and reason about end-to-end AI systems, including data pipelines, model interactions, and infrastructure at scale.

Large-Scale Program Design: The ability to scope, structure, and plan complex, multi-faceted research programs that may span multiple quarters or years.

Advanced Theoretical Modeling: The capacity to engage with, critique, and contribute to the deep theoretical underpinnings of machine learning.

 

Experience:- 5+ Years

Education:- PhD Track or PhD

 

Competencies for Success

Strategic Thinking: Defines long-term research roadmaps that anticipate future business needs and technological shifts, ensuring AI strategy creates a sustainable competitive advantage.

Influence & Leadership: Inspires and guides teams (often without direct authority) toward a compelling technical vision, driving consensus among senior leaders on critical decisions.

Navigating Ambiguity: Thrives in and provides clarity to highly unstructured and high-risk problem spaces, confidently defining the path forward where none exists.

Business Acumen: Demonstrates a deep, intuitive understanding of the market, product viability, and financial implications of research, consistently connecting scientific work to business impact.

Scientific Diplomacy: Skillfully manages and resolves high-stakes scientific debates and technical conflicts, fostering a collaborative and intellectually rigorous environment.

Organizational Impact: Looks beyond their own team to identify and drive improvements in technology, processes, and culture that benefit the entire R&D organization.