Senior NLP engineer

Verigram is an international AI company focused on digital identity and fraud prevention. Our solutions are used by banks, fintechs, and online platforms to onboard users remotely and prevent fraud.

And now we are looking for a Senior NLP Engineer who can develop Conversational AI from idea generation to implementation in high-load production. This role is perfect if you love building LLM systems, quality assurance processes and high-load AI services used by thousands of real users. We’re building systems that are capable of independently solving business-related problems: knowledge base search, summarization, extracting insights from requests, proactively providing assistance to operators and AI-powered automation.

We build production-ready AI systems that process large-scale data every day:

1. Face biometrics and liveness detection
2. Real-time video analytics
3. AI assistants and RAG systems
4. High-load ML services used by thousands of users

What you will do:

• Design, train, fine-tune, and evaluate machine learning and deep learning models.
• Develop solutions using LLMs, NLP, computer vision, or other modern AI architectures.
• Build and improve datasets, including data cleaning, labeling strategies, augmentation, and synthetic data generation.
• Design experiments and define appropriate evaluation metrics.
• Improve model accuracy, robustness, latency, and computational efficiency.
• Research and evaluate new models, architectures, papers, and AI technologies.
• Work with ML Engineers to productionize models and build reliable inference pipelines.
• Work closely with business to identify opportunities for AI/ML, define success metrics, and drive product decisions based on data and experimentation.
• Participate in model monitoring, retraining, and continuous improvement of deployed ML systems.
• Contribute to technical decisions and ML best practices

Engineering culture:

• Participate in architecture decisions

• Code reviews and documentation

• Contribute to ML engineering best practices

Tech stack:

Python • PyTorch • FastAPI • Transformers• Docker
LangChain • LangGraph • RAG • ClearML • CUDA

Must-have

• 5+ years of experience in Machine Learning, Data Science, Applied AI, or related fields.
• Strong knowledge of machine learning, deep learning, probability, statistics, and optimization.
• Strong Python skills.
• Strong practical experience with PyTorch or a comparable deep learning framework.
• Experience training and fine-tuning neural networks.
• Experience with modern model architectures such as Transformers, LLMs, VLMs, depending on the problem domain.
• Ability to read research papers and translate relevant ideas into practical implementations.
• Experience shipping ML models to production
• Practical experience building AI agents and LLM pipelines using LangChain / LangGraph
• Understanding of the full ML lifecycle
• Experience with Git, Linux, Docker, and common ML development workflows.
• Good communication skills and ability to explain technical decisions clearly.
• Ability to translate undefined business objectives into technical plans, articulate architectural decisions, and highly self-managed

Nice to have:

• Experience building high-load services

• Experience in backend development

• Experience with GPU inference

• Experience in developing AI agents and knowledge of LLMOps principles, including CI/CD, orchestration, and prompt version control.

• Understanding the security of LLM applications.

• Experience developing and launching BERT, Sentence-BERT, T5 or traditional architectures (fasttext, word2vec)

• Experience with experiment tracking tools such as MLflow, ClearML, Weights & Biases, or similar.

What we offer:

• Real production ML & LLM projects

• Access to GPU infrastructure

• Strong impact on AI product architecture

• Competitive salary

• Strong engineering culture, low bureaucracy

Join us to build real-world AI products!