Senior AI/ML Engineer

Circle K is hiring for an AI/ML engineering role focused on building agentic AI systems and classic machine learning solutions. The company has an internal whistleblower notification procedure and promotes a diverse and inclusive culture. The job is based in Warszawa, Poland.

• Bachelor's or master's degree in Computer Science, Machine Learning, or related field (or equivalent)
• 5+ years experience building and deploying ML models in production
• Strong programming skills in Python
• Familiarity with ML frameworks: PyTorch, TensorFlow, scikit-learn
• Experience building and deploying agents on major AI platforms (Azure AI Foundry, Google Vertex AI / Gemini, Anthropic Claude)
• Experience with LLM APIs and prompt engineering (OpenAI, Anthropic, Google)
• Familiarity with vector databases and RAG architectures (Pinecone, Weaviate, Chroma)
• Experience with computer vision or image recognition models in production
• Solid software engineering fundamentals: version control, testing, API design
• Experience with cloud platforms (AWS, GCP, or Azure)

Preferred Qualifications:

• Experience building agents on Azure AI Foundry Agent Service and/or Google Vertex AI Agent Builder
• Familiarity with cross-platform agent portability and multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI)
• Experience designing agentic systems combining perception and reasoning layers
• Background in reinforcement learning or fine-tuning LLMs (LoRA, RLHF)
• Experience with containerization and orchestration (Docker, Kubernetes)
• Contributions to open-source ML/AI projects
• Familiarity with evaluation frameworks for LLM/agent outputs
• Experience optimizing models for on-device or edge deployment (mobile/tablet)

Agentic AI & LLM Systems (Core Focus):

• Design and build agentic workflows using LLMs for autonomous multi-step tasks
• Deploy agentic solutions across AI platforms like Azure AI Foundry, Google Cloud Vertex AI / Gemini, and Anthropic Claude
• Develop integrations connecting agents to APIs, databases, and internal systems
• Implement orchestration patterns for complex task automation
• Build retrieval-augmented generation (RAG) pipelines
• Establish monitoring for agent reliability and safety
• Prototype agent behaviors using frameworks such as LangGraph, LlamaIndex, CrewAI
• Design workflows consuming outputs from perception/detection models (e.g., computer vision)

Model Development & MLOps:

• Design, train, fine-tune, and evaluate machine learning and deep learning models including computer vision/object detection
• Build and maintain scalable data pipelines
• Implement MLOps practices: CI/CD, versioning, monitoring, retraining
• Optimize model performance and latency
• Design pipelines for discrepancy flagging and downstream automation
• Improve model accuracy using feedback and active learning

Applied Engineering:

• Collaborate with product and design teams to translate business needs into AI features
• Integrate ML models and agents via robust APIs
• Write clean, maintainable, documented code
• Conduct A/B tests and evaluations

Collaboration & Communication:

• Work with AI Platform Architect to align with technical standards and strategy
• Partner with business stakeholders to define success metrics
• Collaborate with data engineers, product managers, domain experts
• Communicate technical trade-offs to technical and non-technical audiences
• Stay current with ML, LLM, and agentic architecture research

The company has an Internal Notification and Follow-up Actions Procedure regarding whistleblower reports. The offer emphasizes a strict non-discrimination policy based on race, national origin, gender, sexual orientation, disability, age, or other legally protected status.