Middle Machine Learning Engineer (AI)

TL;DR

Middle Machine Learning Engineer (AI/LLMOps): Building and maintaining end-to-end ML systems and LLMOps tooling with an accent on NLP, RAG, and agentic workflows. Focus on implementing data pipelines, model observability, and developing autonomous AI applications using LangGraph and CrewAI.

Location: Must be based in Poland (Remote/Office)

Company

hirify.global is a global digital transformation company and a leader in AI and Data Science services.

What you will do

• Implement and maintain end-to-end ML pipelines for data ingestion, feature engineering, and production deployment.
• Build LLMOps pipelines using MLflow, Langfuse, or LangSmith to ensure model observability, reproducibility, and prompt versioning.
• Develop agentic systems and multi-agent workflows using frameworks such as LangGraph or CrewAI.
• Collaborate with Data Scientists and architects to deliver production-ready NLP, RAG, and multimodal AI solutions.
• Optimize ML infrastructure using CI/CD pipelines across AWS, Azure, or GCP environments.
• Configure workflow orchestration pipelines using Kubeflow, Airflow, or Databricks Workflows.

Requirements

• At least 2 years of hands-on experience building and deploying ML solutions in Cloud production environments.
• Strong Python proficiency within the data science and ML ecosystem.
• Experience with LLMOps and experiment tracking tools like MLflow, Langfuse, or LangSmith.
• Understanding of CI/CD for ML and orchestration tools such as Kubeflow or Airflow.
• Knowledge of cloud-based AI/ML services (AWS, Azure, or GCP).
• English: Upper-intermediate (B2) or higher proficiency required.
• Location: Based in Poland.
• Master’s degree in Computer Science or a related field.

Culture & Benefits

• Work within a dedicated AI and Data Science Center of Excellence alongside 170+ ML engineers and architects.
• Engagement with cutting-edge projects involving RAG, multimodal AI, and autonomous agents.
• Inclusive work environment as an Equal Opportunity Employer.
• Flexible work format allowing for both remote and office-based collaboration.