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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 MLOps 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
• AI assistants and RAG systems
• High-load ML services used by thousands of users

What you will do:

• Develop ML services using FastAPI
• Containerize and deploy models
• Set up CI/CD
• Optimize GPU inference and performance
• Build batch and real-time inference pipelines for LLMs and other models
• Work with R&D and backend teams

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

• Experience in MLOps / DevOps / Backend 2 - 4 years
• Experience shipping ML models to production
• Understanding of the full ML lifecycle
• Strong level of knowledge of Python, FastAPI, Docker, Linux, SQL
• Experience in CI / CD

Nice to have:

• Experience with LLMs / RAG / embeddings
• Inference optimization experience
• Experience building high-load services
• Experience in backend development
• Experience with GPU inference
• Experience in setting up model monitoring

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!