About Us

Adalat AI is a legal-tech startup revolutionizing the Indian judicial system through advanced artificial intelligence solutions, by building an end-to-end justice tech stack. Operating across 10 Indian states and supported by some of the world's largest foundations, we're dedicated to eliminating judicial delays and enhancing access to justice through innovative technology.

Our solutions, including state-of-the-art ASR models for Indian languages, have been successfully implemented in multiple high courts, with our recent launch at the Delhi High Court marking a significant milestone. Founded by a team combining expertise in law, technology, and computational linguistics, with credentials from Harvard, Oxford, Cambridge, MIT, IITs, IIIT Hyderabad, Adalat AI has earned recognition through prestigious competitions and partnerships, demonstrating our commitment to bringing India's courts into the digital age alongside other modernized systems like UPI, Aadhaar, and online taxation.

About the Role

This is a full-time position focused on optimizing Adalat AI’s Legal Intelligence product to ensure efficient and cost-effective deployment across diverse hardware platforms. As an early member of the team, you will:

• Collaborate closely with the founding team to enhance model performance, enabling seamless operation for judges and stenographers.
• Identify and implement innovative solutions to optimize machine learning models for various hardware architectures, including CPUs and GPUs.
• Work in close collaboration with cross-functional partners in design, backend, and frontend functions.
• Solve complex problems related to model efficiency and scalability.
• Build cost-effective and scalable systems that can operate efficiently in resource-constrained environments.

Responsibilities

• Design and implement optimization techniques for text processing systems using machine learning and deep learning, focusing on English and Indic Languages.
• Analyze and optimize model execution paths to improve latency and power consumption.
• Develop and apply model compression methods such as quantization, pruning, and distillation to enhance performance on diverse hardware platforms.
• Collaborate with hardware and platform architecture teams to ensure compiler support for next-generation features.