DevOps/MLOps Engineer (Python Focus)

About Laniqo/PONS Intelligence

Laniqo/PONS Intelligence is a cutting-edge AI company specializing in Neural Machine Translation and Natural Language Processing. Born as a spin-off from Adam Mickiewicz University (UAM) and PONS Langenscheidt GmbH, we combine academic experience with market business solutions.

We don't just use AI; we advance it. Our team regularly publishes research at top conferences like ACL and WMT, and our know-how powers domain-specific translation for industry giants like Allegro. We are building intelligent, self-adapting translation systems that bridge language barriers.

The Role

We are looking for a DevOps/MLOps Engineer with strong Python Backend skills to join our engineering team. In this role, you will be the bridge between our Research Team (creating state-of-the-art AI solutions) and our Product Team (delivering reliable, scalable APIs).

You will focus on building robust infrastructure, automating deployment pipelines, and ensuring our AI solutions perform at high speed and scale.

Key Responsibilities

• MLOps & Model Serving: Optimize model inference for low latency and high throughput.

• Infrastructure Management: Build and maintain scalable infrastructure (using Docker, Kubernetes, and Cloud Providers) to support our services.

• Backend Development: Develop and optimize Python-based APIs (FastAPI) and tools that expose our solutions to end customers.

• CI/CD Automation: Implement and improve CI/CD workflows to ensure code quality and rapid deployment cycles.

• Collaboration: Collaborate with ML Researchers to productize state-of-the-art models, ensuring their seamless integration and deployment into customer applications.

• Monitoring & Reliability: Ensure high availability of our services and set up monitoring solutions for both system metrics and model performance.

What We Are Looking For

• Python Proficiency: Strong experience in Python development, particularly in building backend services (REST APIs).

• DevOps Mindset: Solid experience with containerization (Docker) and orchestration (Kubernetes).

• MLOps Exposure: Experience or strong interest in deploying Machine Learning models (e.g., using vLLM, Triton Inference Server, TorchServe, or similar). Understanding of the ML lifecycle.

• Cloud Experience: Familiarity with cloud platforms (AWS, GCP, or Azure) and Infrastructure as Code (Terraform/Ansible).

• Database Knowledge: Experience with SQL databases.

• Problem Solver: Ability to debug complex distributed systems and optimize performance.

Nice to Have

• Experience with GPU computing and optimizing deep learning models for inference.

• Experience with vector databases (Qdrant, Pinecone, Milvus or similar)

• Experience with ArgoCD or similar GitOps tools.

• Familiarity with NLP technologies or Machine Translation systems.

• Interest in keeping up with the newest AI tools.

What We Offer

• Growth: A unique opportunity to work alongside academic researchers and industry experts.

• Knowledge Sharing: We value education—participate in internal workshops and research discussions.

• Flexibility: Hybrid work model from our office in the heart of Poznań (ul. Zwierzyniecka 3).

• Culture: A flat structure, open communication, and a friendly environment born from a mix of university and business roots.

• Medical Care: Luxmed private medical care

Interview Process

• 30 minutes initial recruiter interview

• 45 minutes technical scoping interview

• 45 minutes mindset and cultural fit interview