Compliance Engineering - Neon Platform - Vice President - Bengaluru
On-siteBengaluru, Karnataka, India
Job Summary
Design and develop scalable, end-to-end AI/ML solutions for compliance applications, including GenAI-driven agentic frameworks, RAG pipelines, and embeddings for knowledge bases. Explore diverse problems through model fine-tuning, prompt engineering, and experimentation to address novel business challenges. Develop, test, and maintain high-quality, production-ready code while driving technical deliverables from design through implementation. Collaborate with compliance officers, legal counsel, and stakeholders to translate business requirements into technical solutions, and participate in code reviews to ensure quality and adherence to standards. Stay current with latest advancements in AI/ML platforms to solve complex business problems.
Required Qualifications
- A Bachelor's, Master's or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study
- Minimum 6+ 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
- Experience working with embedding models and vector databases
- Experience with MLOps practices, including model deployment, containerization (Docker, kubernetes), CI/CD, and model monitoring
- 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
Desired Qualifications
- Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems
- Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation
- Experience with model interpretability techniques
- Prior experience in code reviews/ architecture design for distributed systems
- Experience with data governance and data quality principles
- Familiarity with financial regulations and compliance requirements
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