Natural Language Processing Engineer

Perfios is a leading B2B SaaS TechFin company empowering 1,000+ financial institutions across

18+ countries with AI-driven financial insights and decision-making. We process over 8 billion

data points annually and are now expanding our innovation footprint through advanced AI/ML

and data science applications in credit, fraud, and decision intelligence.

We are seeking a motivated Python Developer / NLP Engineer with 2+ years of experience to

join our Data Science NLP team. The ideal candidate will be skilled in building data pipelines,

creating and refining datasets, designing rule-based extractors, and applying fundamental data

science practices. This role requires a balance of hands-on engineering skills, problem-solving

mindset, and the ability to think in terms of building scalable, production-ready products.

Key Responsibilities:

• Build and maintain robust data pipelines for model training, evaluation, and execution

workflows

• Create, clean, and augment datasets for NLP model development and testing
• Develop and refine rule-based extractors and regex patterns for entity and information

extraction tasks

• Apply models to real-world use cases and integrate them into production systems
• Design and implement rule-based engines for text processing and information extraction
• Apply and test fundamental data science techniques, including interpreting model test

reports and performance metrics

• Collaborate with ML engineers and data scientists to integrate datasets, extractors, and

models into larger NLP pipelines and products

• Write clean, efficient, and well-structured Python code for data processing,

experimentation, and prototyping

• Troubleshoot issues in models and pipelines with a practical, problem-solving approach
• Contribute to product-oriented thinking, ensuring solutions are scalable, maintainable,

and production-ready

• Stay up-to-date with emerging techniques in NLP, dataset curation, and applied ML

Required Qualifications:

Education:

Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a

related field

2+ years of experience with Python programming and applied NLP.

Technical Skills

Strong hands-on experience in dataset creation, labeling, cleaning, and

augmentation

Solid foundation in NLP fundamentals (tokenization, embeddings, NER, text

classification, entity extraction, etc.)

Proficiency in building data pipelines for training, evaluation, and model

deployment

Strong expertise in rule-based systems, regex patterns, and information

extraction techniques

Basic knowledge of data science and ML workflows, including model evaluation

and test reporting

Proficiency with common NLP/ML libraries (e.g., spaCy, NLTK, Hugging Face

Transformers, scikit-learn, pandas)

Experience with PyTorch or TensorFlow for model implementation and inference

Strong knowledge of data structures and algorithms

Familiarity with SQL/NoSQL and data manipulation

Understanding of version control systems like Git

• Core Competencies

Strong problem-solving skills with the ability to apply first-principles thinking to

real-world scenarios

Software engineering mindset comfortable writing production-quality code,

debugging issues, and designing scalable solutions

Ability to work with both structured and unstructured textual data

Strong attention to detail in data quality and pipeline reliability

Preferred Skills (Good to have):

• Experience with prompt engineering, agent building, fine-tuning LLMs, and integrating

generative AI models into production systems

• Exposure to retrieval-augmented generation (RAG) and vector search pipelines
• Familiarity with multi-agent orchestration frameworks (LangChain, LangGraph, or

similar)

• Experience with MLOps concepts and tools for model deployment and monitoring
• Familiarity with containerized deployments using Docker
• Working knowledge of cloud platforms (AWS, GCP, Azure)
• Experience with CI/CD pipelines
• Understanding of traditional ML algorithms and their applications