About Perfios :

Founded in 2008, Perfios is a global B2B SaaS fintech company serving the Banking, Financial Services and Insurance industry in 18 countries, empowering 1000+ Financial Institutions.

Through its pioneering software platforms and products, Perfios helps Financial Institutions take big leaps by shaping their origination, onboarding, decisioning, underwriting and monitoring processes at scale and speed.

Funding :

Perfios secured $80 Million from Teachers' Venture Growth in March 2024. Earlier in FY 23-24, $229 Million was raised in Series D, and $70 Million in Series C in February 2022. Total funding raised is $435.1 Million.

Role Overview :

- Lead and manage a high-performing team of Data Scientists and Software Engineers.

- Collaborate with product managers, engineering teams, and business stakeholders to translate business requirements into scalable NLP and Generative AI solutions.

- Oversee end-to-end delivery of data science projects, set project priorities, lead sprint meetings, and ensure quality assurance.

- Explore research papers, design synthetic data pipelines, and data augmentation techniques.

- Devise and execute ML/DL/NLP/GenAI experiments and optimize models for production inference.

Must Have Skills :

- 7+ years of relevant experience.

- Strong theoretical foundation in Embeddings, classical ML, Deep Learning, RNNs, LSTMs, GRUs, and Transformer architectures.

- Proficiency in Python and modern AI/DL frameworks (PyTorch, TensorFlow).

- Hands-on experience with Generative AI models and core NLP techniques (NER, Sentiment Analysis, Text Classification).

- Proven expertise in Generative AI product implementations using open-source and proprietary LLMs.

Good to Have :

- Experience with RAG architectures, vector databases (FAISS, Weaviate, Chroma), and multi-agent orchestration (LangGraph, LangChain).

- Expertise in fine-tuning SLMs/LLMs using LoRA, QLoRA, PEFT.

- Knowledge of inference optimization techniques.

Leadership Responsibilities :

- Mentor and guide a team of Data Scientists and Software Engineers.

- Manage project timelines, deliverables, and resource allocation.

- Drive best practices in code quality, MLOps, and model evaluation.