Conseiller.ère ML/IA

Job summary

Design, develop, and deploy production-level machine learning and generative AI systems, including LLM-based solutions and RAG architectures. Manage the full ML lifecycle, from building training pipelines to monitoring performance, bias, and operational costs in production.

Job details

Design, develop, and deploy production-level machine learning and generative AI systems, including LLM-based solutions and RAG architectures. Manage the full ML lifecycle, from building training pipelines to monitoring performance, bias, and operational costs in production. Requires a Bachelor's or Master's degree in Computer Science, Engineering, or Data Science with over 6 years of engineering experience, including at least 3 years in AI/ML. Proficiency in Python and major ML frameworks like PyTorch and TensorFlow is essential.

What you’ll do

Design, develop, and deploy production-level machine learning and generative AI systems, including LLM-based solutions and RAG architectures. Manage the full ML lifecycle, from building training pipelines to monitoring performance, bias, and operational costs in production.

Requirements

Requires a Bachelor's or Master's degree in Computer Science, Engineering, or Data Science with over 6 years of engineering experience, including at least 3 years in AI/ML. Proficiency in Python and major ML frameworks like PyTorch and TensorFlow is essential.

Benefits

• 4 weeks of cumulative vacation from day one • Flexible working hours • Professional development allowance (PDA) for training, equipment, and physical activities • Expertise-based training • Registered Retirement Savings Plan (RRSP) with employer contribution up to 3% • Modular group insurance plan • Public transport or parking reimbursement • Referral bonuses • 11 public holidays • Personal days • Active social life (happy hours, social club, healthy snacks, coffee)

Listed skills

• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Generative AI
• Python
• PyTorch
• TensorFlow
• Scikit-learn
• LLM
• RAG Architecture
• CI/CD Pipelines
• Feature Engineering
• Model Deployment
• MLOps
• Data Science
• Model Monitoring
• Inference Optimization
• AI Security

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Consulting

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