Techincal Lead

About Us :

BharatGen, a government funded project and a part of the TIH-IoT initiative, is at the forefront of Generative AI innovation, dedicated to addressing India's unique challenges through cutting-edge technology. Our mission is to develop a suite of generative AI technology and solutions that capture and reflect the rich linguistic, cultural, socio-economic, and industry-specific diversity of India, driving meaningful impact across millions of lives and various sectors nationwide. As the Generative AI Tech Lead, you will play a pivotal role in advancing AI innovation by developing foundational models and scalable applications that solve complex technical challenges. You'll be joining a multidisciplinary team of top researchers and engineers from leading institutions and industries, working together to drive meaningful change. This is more than just a career move-it's an opportunity to shape the future of AI in India and contribute to a project of national significance.

Job Summary :

We are seeking an accomplished and technically adept Generative AI Tech Lead with deep expertise in the development, optimization, and deployment of large-scale generative AI models, particularly in text and speech domains. This role involves building foundational models, and creating advanced applications and solutions that address the complex technical challenges of large-scale model development. Your leadership will be instrumental in driving the development of impactful AI technologies, tailored to India's diverse linguistic landscape.

Key Responsibilities :

Technical Leadership :

- Lead, mentor, and inspire a team of AI researchers and engineers, fostering a culture of innovation and technical excellence.

- Define and execute the technical roadmap and strategy for generative AI projects, ensuring alignment with organizational goals.

- Architect, develop, and optimize large-scale generative AI models, focusing on foundational models and their practical applications in text and speech domains.

- Lead the design and implementation of robust training and inference pipelines, ensuring scalability, efficiency, and adaptability, particularly for multilingual and multi-dialectal text and speech models.

- Drive innovation by experimenting with state-of-the-art techniques in NLP, speech recognition, and generative language models, developing solutions that address real-world challenges.

- Refine AI infrastructure to support the deployment of optimized models, with a focus on low latency, high throughput, and cost efficiency, especially for large-scale models with billions of parameters.

- Implement and experiment with advanced optimization techniques such as quantization, distillation, sparsity, and model compression to enhance performance and Development & Application :

- Oversee the end-to-end development of text and speech foundational models and their deployment into scalable AI applications and solutions.

- Tackle complex technical challenges related to large-scale model development, including optimization for performance, latency, and resource efficiency.

- Utilize cutting-edge tools and frameworks like PyTorch, TensorFlow, DeepSpeed, and CUDA to build, deploy, and scale AI models and applications capable of handling diverse linguistic data across modalities.

- Lead innovation in advanced NLP and speech processing techniques, including transformers, fine-tuning of language models, and the development of next-generation generative models.

- Develop and integrate model management systems, including version control, reproducibility, and lineage tracking, ensuring robust and reliable AI model deployment.

- Focus on real-time monitoring, model drift detection, and continuous performance enhancement post-deployment, leveraging advanced MLOps practices.

Infrastructure & Deployment :

- Optimize AI infrastructure for large-scale training and inference, leveraging GPU clusters, cloud platforms, custom hardware configurations, and advanced orchestration frameworks like SLURM and Kubernetes.

- Integrate and tailor advanced MLOps frameworks such as KubeFlow, MosaicML, and Terraform to support robust development, deployment, and monitoring cycles for AI applications.

Research & Innovation :

- Stay at the forefront of AI research in the text and speech domains, applying new techniques to solve complex technical challenges specific to Indian languages and dialects.

- Lead research initiatives focused on cutting-edge NLP and speech processing innovations, with an emphasis on techniques like sparsity, model pruning, and knowledge distillation to enhance the efficiency and effectiveness of large-scale AI models.

- Foster a culture of continuous experimentation, encouraging the use of emerging AI techniques and frameworks to push the boundaries of what's possible in generative AI, particularly in the Indian context.

Collaboration :

- Collaborate closely with other technical teams to ensure seamless integration of AI models and applications into the broader technology stack, particularly in contexts relevant to India's diverse landscape.

- Work with product teams to translate national and regional needs into technical solutions, ensuring that the AI models and applications developed have practical, real-world impact.

- Foster a collaborative and innovative team environment.

Project Management :

- Oversee the end-to-end lifecycle of AI projects, from ideation to deployment, ensuring that each project aligns with strategic objectives and delivers measurable outcomes.

- Coordinate with product managers, data scientists, and engineers to ensure the timely and successful delivery of AI solutions.

- Monitor project progress, identifying and mitigating risks, and adjust plans as necessary to meet objectives and deadlines.

Education :

- Ph.D. in Computer Science, AI/ML, or a related field with 5+ years of relevant experience, or an MS with 8+ years of experience in applied AI/ML.

Experience :

- Extensive hands-on experience in developing and deploying large-scale generative AI models and their applications, particularly in the text and speech domains.

- Proven expertise in high-performance computing, with proficiency in Python, C/C++, CUDA, and the optimization of NLP and speech models.

- Strong track record in optimizing AI models for training, inference, and real-world applications, with practical knowledge of tools like DeepSpeed, FSDP, and advanced MLOps frameworks.

- Demonstrated success in leading AI projects and teams, with a focus on delivering innovative solutions in dynamic environments.

Skills :

- Deep understanding of generative AI techniques specific to NLP and speech processing, including transformers and advanced language models.

- Strong programming skills in Python, C/C++, with deep experience in GPU acceleration, CUDA, and kernel-level programming for AI applications.

- Experience with advanced optimization and acceleration techniques, including quantization, distillation, and model compression.

- Proficiency with cutting-edge AI frameworks and tools, including DeepSpeed, FSDP, and advanced MLOps platforms like KubeFlow and Terraform.

- Familiarity with large-scale model management, including version control, model lineage tracking, and real-time monitoring in production environments.

- Exceptional problem-solving abilities with a focus on innovation, efficiency, and the development of scalable AI solutions.

- Strong communication and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences.

- Ability to thrive in a fast-paced, dynamic environment, managing multiple priorities and driving results.

Preferred Qualifications :

- Experience with developing and deploying speech/text-based large-scale deep models in production environments.

- Familiarity with the latest advancements in NLP and speech processing research, particularly in the context of Indian languages and dialects.

- A strong publication record in top-tier AI conferences or journals is a plus.