Director Applied Science

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟴𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟭𝟲𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟴𝟬-𝟭𝟲𝟬 𝗟𝗣𝗔)

Experience: 16+ yrs

Location: Bengaluru

We are seeking an accomplished Director of Applied Science to lead advanced machine learning and artificial intelligence initiatives that drive innovation, improve business outcomes, and expand the capabilities of data-driven products and services. The ideal candidate will combine deep technical expertise, strategic leadership, and a strong track record of delivering production-grade AI/ML solutions.

This role requires an experienced leader who can define the applied science vision, guide research and experimentation, and translate scientific advancements into scalable business applications. You will lead applied scientists and machine learning engineers, establish technical standards, and collaborate with Product, Engineering, and Data teams to deliver measurable business impact.

Requirements

Key Responsibilities

• Lead and develop a team of applied scientists and machine learning engineers building advanced models, algorithms, and AI-powered solutions.
• Define the technical vision, research strategy, and roadmap for applied science initiatives in alignment with business priorities.
• Identify opportunities to apply machine learning, deep learning, and advanced analytics to complex business problems.
• Oversee experimentation, model development, evaluation, validation, and deployment into production environments.
• Guide the development of supervised, unsupervised, and deep learning solutions for real-world applications.
• Partner with Product, Engineering, and Data teams to integrate ML models into scalable, reliable, and high-performance systems.
• Establish best practices for scientific experimentation, statistical validation, reproducibility, model monitoring, and continuous improvement.
• Champion responsible AI principles, including model transparency, fairness, reliability, and appropriate risk management.
• Evaluate emerging research, algorithms, and technologies to identify opportunities for innovation and competitive advantage.
• Ensure projects are delivered within agreed timelines and scope while maintaining technical quality and business relevance.
• Monitor project progress, manage technical risks, remove blockers, and prioritise resources across multiple initiatives.
• Mentor scientists and engineering leaders, strengthen technical capabilities, and foster a culture of innovation and continuous learning.
• Define success metrics and evaluate the business impact of applied science initiatives.
• Represent the applied science function in executive discussions, strategic planning, and technology roadmap decisions.

What Makes You a Great Fit

• 16+ years of experience in applied science, machine learning, artificial intelligence, or related technical fields.
• At least 3 years of experience in a management or technical leadership role, leading scientific or ML engineering teams.
• A PhD or Master's degree in Machine Learning, Computer Science, Statistics, or a related discipline.
• Proven experience building, deploying, and scaling machine learning models in production systems.
• Deep understanding of supervised learning, unsupervised learning, deep learning, and advanced modelling techniques.
• Strong programming skills in Python and hands-on proficiency with frameworks such as PyTorch or TensorFlow.
• Experience leading research-driven initiatives and translating scientific findings into practical product or business solutions.
• Strong understanding of model evaluation, experimentation, statistical validation, and production ML lifecycle practices.
• Demonstrated ability to define technical strategy, manage complex projects, and deliver measurable business outcomes.
• Excellent people leadership, mentoring, and team development capabilities.
• Strong communication and stakeholder-management skills, with the ability to engage technical teams and executive leadership.
• A strategic, analytical, and innovation-oriented mindset with a commitment to scientific rigour and responsible AI.