Website:
perfios.ai
Job details:
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. Perfios delivers 8.2 Billion Data Insights to Financial Institutions every year to facilitate faster decisioning, and processes 1.7 Billion Transactions a year with an AUM of 3 Trillion, significantly accelerating access to credit and financial services for their clients' customers. Headquartered in Bangalore, Perfios has offices worldwide and with 75+ products and platforms, and over 500+ APIs. In Perfios, its clients have a confidant and a robust start-to-end tech platform.
Funding:
Perfios secured $80 Million from Teachers’ Venture Growth, the late-stage venture and growth investment arm of the Ontario Teachers’ Pension Plan in March 2024. Earlier in FY 23-24, $229 Million was raised by Perfios in their Series D round from Kedaara Capital, marking the largest fund raise among Indian B2B SaaS companies for this financial year. Prior to this, Perfios raised $70 Million in Series C round from Warburg Pincus and Bessemer Venture Partners in February 2022. The latest round of funding has taken the total funding raised by Perfios to $435.1 Million.
Key Metrics:
75 Million bank statements processed annually
3 Trillion in loans processed for Banks & Financial Institutions per year
1.5 Trillion API requests processed annually
200+ Infosec audits per year
0 Infosec violations since inception
99.9% Uptime with 0 SLA violations
Current Employees: 1400+
Website: https://www.perfios.com
Role Overview & What your average day would look like:
- Lead and manage a high-performing team of Data Scientists and Software Engineers.
- Collaborate closely 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/team meetings, and ensure quality assurance of deliverables.
- Explore research papers, open-source codebases, and design synthetic data pipelines and data augmentation techniques for NLP tasks.
- Devise and execute ML/DL/NLP/GenAI experiments, analyze failure patterns, and refine model architectures, loss functions, and data strategies.
- Optimize models for production inference and collaborate with software engineering teams for deployment and scaling.
Must Have Skills & Technical Expertise:
- Strong theoretical foundation and hands-on experience with Embeddings, classical ML, Deep Learning models, RNNs, LSTMs, GRUs, and Transformer architectures.
- 5+ yrs of relevant experience.
- Proficiency in Python and modern AI/DL frameworks (PyTorch, TensorFlow).
- Hands-on experience working with Generative AI models.
- Practical experience with core NLP techniques and tasks, including Named Entity Recognition (NER), Sentiment Analysis, Text Classification, Information Extraction, etc.
- Proven expertise in Generative AI product implementations using both open-source and proprietary LLMs.
- Ability to translate cutting-edge research concepts into scalable, real-world production solutions in a team setting.
Good to Have / Preferred Skills:
- Inference optimization techniques for scaling AI systems in production environments.
- Hands-on experience with Retrieval-Augmented Generation (RAG) architectures, vector databases (FAISS, Weaviate, Chroma, LanceDB), and tool-augmented agents.
- Proven expertise in multi-agent orchestration frameworks (LangGraph, MCP, LangChain, or custom solutions).
- Deep understanding of Transformer internals (attention mechanisms, KV caching, speculative decoding, RoPE, etc.).
- Proven expertise in fine-tuning and optimizing SLMs/LLMs using techniques like LoRA, QLoRA, PEFT, etc.
Leadership & Managerial Responsibilities:
- Lead, mentor, and guide a team of Data Scientists and Software Engineers, providing technical supervision, conducting code reviews, and supporting career development.
- Manage project timelines, team deliverables, and resource allocation across cross-functional initiatives.
- Act as the technical lead and key liaison between product management, engineering, and data science teams.
- Drive best practices in data science code quality, MLOps, model evaluation, and deployment, fostering a culture of continuous learning and innovation.
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