Middle ML 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 an ML Engineer who can take models from research → production → scale. This role is perfect if you love building LLM systems, computer vision pipelines and high-load AI services used by thousands of real users.

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

- Face biometrics and liveness detection

- Document verification and KYC/AML

- Real-time video analytics

- LLM assistants and RAG systems

- High-load ML services used by thousands of users

What you will do:

LLM / Generative AI

- Fine-tune open-source LLMs (LoRA / PEFT)

- Build and scale production RAG systems

- Develop embedding and vector search pipelines

- Build AI assistants and internal AI tools

- Prompt engineering and evaluation pipelines

- Run A/B testing and LLM experiments

- Optimize inference (latency / throughput / GPU)

Data & ML Pipelines

- Build ETL/ELT pipelines for ML

- Data validation and dataset versioning

- Automate model training and retraining

- Experiment tracking and quality metrics

ML Infrastructure & Production

- Develop ML services using FastAPI

- Containerize and deploy models

- Optimize GPU inference and performance

- Build batch and real-time inference pipelines

Monitor models:

- data/model drift

- quality degradation

- latency and reliability

Engineering culture:

- Participate in architecture decisions

- Code reviews and documentation

- Contribute to ML engineering best practices

Tech stack:

Python • PyTorch • FastAPI • PostgreSQL • Redis • Kafka • Docker
LangChain • LangGraph • RAG • Vector Search • GPU inference

Requirements:

Must-have

- 2–4 years of experience in ML / DL / NLP

- Experience shipping ML models to production

- Strong Python skills (backend + ML)

- Hands-on experience with PyTorch

- Understanding of the full ML lifecycle

Nice to have:

- Experience with LLMs / RAG / embeddings

- Inference optimization experience

- Experience building high-load services

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!