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Job Summary: The VP - Machine Learning will lead a team of 20-40 engineers, including both senior and junior talent, to build and scale foundational models that define the next generation of AI applications in India. This role combines deep technical expertise with strategic leadership, requiring someone who can navigate the evolving landscape of AI research while delivering production-ready solutions at scale. Key Responsibilities: 1.Strategic Leadership and Vision Develop and execute comprehensive ML/AI strategies aligned with BharatGen's mission. Define the technical roadmap for foundational model development across text, speech, and vision modalities. Set clear goals for the engineering organization and ensure alignment with broader company objectives. Collaborate with the CTO and executive team to shape product strategy and business priorities. 2.Team Management and Development Lead and mentor a diverse team of 20-40 ML engineers, data scientists, and researchers across all experience levels. Build high-performing teams through strategic hiring, talent development, and performance management. Foster a culture of innovation, technical excellence, and continuous learning within the organization. Develop career progression pathways for both senior and junior engineers, ensuring knowledge transfer and skill development. 3.Technical Excellence and Innovation Oversee the entire machine learning lifecycle from research to production deployment for foundational models. Incorporate cutting-edge research and emerging trends in AI, particularly in foundation models and multimodal AI systems. Ensure engineering excellence through robust MLOps practices, scalable infrastructure, and production-quality code. Drive innovation in model architecture, training methodologies, and deployment strategies specific to diverse language and cultural contexts. Proficiency in ML frameworks (PyTorch, TensorFlow), distributed training, and MLOps best practices. Understanding of cloud computing platforms and large-scale infrastructure management 4.Research Integration and Industry Trends Stay current with the latest developments in foundation models. Lead initiatives to incorporate multimodal AI capabilities. Evaluate and integrate emerging AI trends, including the shift toward AI-first applications and agentic solutions. Support partnerships with academic institutions and research organizations to maintain technical leadership. 5.Scaling and Operations Build and scale ML platforms and infrastructure to support foundational model development and deployment. Implement best practices for model training, evaluation, and monitoring at enterprise scale. Oversee the development of robust APIs and microservices for seamless integration of ML models into production environments. Ensure efficient resource utilization and cost optimization for large-scale model training and inference. 6.Cross-Functional Collaboration Work closely with product teams to translate business requirements into technical specifications. Collaborate with engineering teams on infrastructure, architecture, and scalability decisions Partner with business stakeholders to ensure ML solutions deliver measurable value and align with market needs. Communicate complex technical concepts to non-technical stakeholders across the organization. Minimum Qualifications and Experience: 1.Education and Experience: Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Artificial Intelligence, or related field. 8+ years of hands-on experience in machine learning and AI, with significant experience in foundational models or large-scale ML systems. 5+ years of leadership experience managing teams of engineers, with a proven track record of scaling technical organizations. Experience in both research and production environments, with understanding of how to bridge academic research and applications. 2.Technical Expertise: Deep expertise in foundational model architectures, training methodologies, and deployment strategies. Strong background in natural language processing, computer vision, and speech processing technologies. Experience with multimodal AI systems and cross-modal learning approaches. Proficiency in ML frameworks (PyTorch, TensorFlow), distributed training, and MLOps best practices. Understanding of cloud computing platforms and large-scale infrastructure management 3.Leadership and Soft Skills: Exceptional leadership and team management capabilities, with experience developing both senior and junior talent. Strong strategic thinking and problem-solving abilities, with a track record of delivering complex technical projects. Excellent communication skills, capable of presenting to both technical teams and executive leadership. Experience with hiring, performance management, and organizational development in fast-growing companies. 4. Preferred Qualifications: Background in developing AI solutions for multilingual or multicultural contexts. Track record of publications in top-tier ML conferences or journals. Experience in startup or high-growth technology environments. Location of work: TIH-IoT, IIT Bombay Campus, Powai, Mumbai 400076. Show more Show less
