AI Engineer – GenAI & Cloud
New
S
SiiAI/ML
Residing in Poland requiredFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Languages
- Fluent English (both written and spoken); Fluent Polish required
- Experience
- At least 4 years in software or ML engineering
- Required Skills
- AWSPythonGCPMicrosoft AzureMLOpsGenerative AILangChain
Requirements
- At least 4 years in software or ML engineering, with hands-on experience shipping AI/ML systems to production.
- Strong Python skills, including writing maintainable, tested code for production services.
- Practical experience with AI/ML frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent.
- Working knowledge of at least one major cloud platform—Azure, AWS, or GCP—and its AI/ML services.
- Experience with vector databases, embedding models, and retrieval systems in real-world applications.
- Familiarity with MLOps fundamentals, including model versioning, experiment tracking, CI/CD for ML, and monitoring.
- Ability to work autonomously and collaborate with architects, data engineers, and product teams.
- Fluent English, written and spoken.
- Fluent Polish.
- Must reside in Poland.
- Nice to have: experience fine-tuning LLMs with LoRA or QLoRA, or working with model training pipelines.
- Nice to have: classical ML experience with scikit-learn, XGBoost, time-series forecasting, or recommendation systems.
- Nice to have: experience with Docker, Kubernetes, and infrastructure as code.
- Nice to have: open-source AI/ML contributions or published technical writing.
Responsibilities
- Build and deploy knowledge-grounded AI systems end-to-end, including data ingestion, chunking, embedding pipelines, retrieval, re-ranking, and response generation.
- Develop agentic applications with tool integrations, planning loops, memory management, and guardrails.
- Implement and maintain ML pipelines for prediction, classification, recommendation, and optimization.
- Deploy and optimize model-serving infrastructure, including API endpoints, batching, caching, GPU utilization, and cost management across cloud environments.
- Write clean, tested, production-grade Python.
- Build evaluation and monitoring pipelines for quality checks, drift detection, latency tracking, and human-in-the-loop feedback.
- Use cloud-native AI services on Azure, AWS, or GCP to implement scalable solutions.
- Collaborate with AI architects on technical design and with data engineers on data availability and quality.
View Full Description & ApplyYou'll be redirected to the employer's site
