Vice President - Machine Learning Compliance Engineering (Bengaluru)
Candidate Experience Site - Lateral
Bengaluru, Karnataka, India
Job Description
Join the Compliance Engineering team, focusing on building AI solutions for compliance applications.
Responsibilities
- Access to petabyte scale of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.
- The opportunity to work with state-of-the-art LLM models and agentic framework.
- A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.
- The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.
- Design and develop scalable and reliable end-to-end AI/ML solutions specifically tailored for compliance applications, ensuring adherence to relevant regulatory requirements. This encompasses the development and implementation of GenAI-driven solutions, including agentic frameworks for automating compliance processes, RAG pipelines, and the creation and utilization of embeddings for compliance knowledge bases.
- Explore diverse AI/ML problems, such as model fine-tuning, prompt engineering, and experimentation with different algorithmic approaches to address novel business challenges.
- Develop, test, and maintain high-quality, production-ready code.
- Drive technical deliverables from design through implementation, contributing strong hands-on engineering and sound technical judgment.
- Collaborate effectively with compliance officers, legal counsel, and other stakeholders to understand business requirements and translate them into technical solutions.
- Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards. Promote best practices for AI/ML development, including version control, testing, and documentation.
- Stay current with the latest advancements in AI/ML platforms, tools, and techniques to solve business problems.
Qualifications
- A Bachelor's, Master's or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.
- Minimum 10+ years AI/ML industry experience for Bachelor’s/Masters, 4+ years for PhD with a focus on Language Models.
- Strong foundation in machine learning algorithms, including deep learning architectures (e.g., transformers, RNNs, CNNs)
- Proficiency in Python and relevant libraries/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn.
- Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
- Strong verbal and written communication skills.
- Curiosity, ownership and willingness to work in a collaborative environment.
- Demonstrated ability to collaborate effectively with peers and contribute in a highly technical, fast-paced engineering environment.
- Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation.
- Prior experience in code reviews/ architecture design for distributed systems.
- Familiarity with financial regulations and compliance requirements.
Nice to have
- Experience with embedding models.