Facilities engineer • ottawa on
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We're hiring an MLOps Engineer to help us take AI prototypes from idea to production-grade service.
Your Responsibilities:
• Implement automated MLOps pipelines (CI/CD, data, training)
• Implement ETL pipelines for data ingestion
• Containerize and deploy models into production
• Continuously monitor models (drift detection, alerting)
• Manage model and data versioning to ensure reproducibility
• Apply governance principles (bias, privacy, transparency)
• Collaborate with data scientists to transform prototypes into stable services
• Write optimized prompts and conduct comparative evaluations of models
You Stand Out With:
• Languages & Libraries: Python + AI libraries (Pandas, Hugging Face, OpenAI, etc.), plus Java and JavaScript experience
• AI Agentic Frameworks: multi-agent systems, ReAct, AutoGen, LangGraph, CrewAI, Chainlit, Streamlit, n8n, Google ADK
• LLM/LFM Knowledge: proprietary models (OpenAI, Claude, Gemini) and open-source models on Hugging Face
• Strong general understanding of data science techniques and pipelines
• Software Architecture: distributed systems, microservices, REST APIs
• Cloud Computing: AWS Bedrock, Azure AI Foundry, GCP Vertex AI
• DevOps/MLOps: CI/CD, Docker, Kubernetes, automated ML workflows, MLflow/DVC versioning, production monitoring (drift, latency, performance, business metrics)
• Governance & Compliance: ethics, bias, GDPR, explainability, AI risk
• Prompt Engineering & Model Benchmarking
• Deployment & Integration: packaging models, API/microservice deployment, backend/legacy integration
• Strong communication skills — able to explain AI challenges clearly to data, product, and infrastructure teams
Interested? Apply directly through this post or send your resume to support@gjitconsulting.com
