AI/ML Architect – Principal
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Role Overview
The Principal AI/ML Architect designs and delivers enterprise-scale AI/ML solutions and leads client-facing delivery across applied AI domains.
The role covers architecture, machine learning, generative AI, cloud platforms, data ecosystems, MLOps, responsible AI, and consulting leadership.
Key Skills for This Role
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About Slalom
Slalom is a business and technology consulting company that partners with clients on strategy, delivery, customer experiences, and modern ways of working.
The company emphasizes purpose, flexibility, connection, recognition, and inclusive collaboration.
Role Overview
The Principal AI/ML Architect designs and delivers enterprise-scale AI/ML solutions and leads client-facing delivery across applied AI domains.
The role covers architecture, machine learning, generative AI, cloud platforms, data ecosystems, MLOps, responsible AI, and consulting leadership.
Core Responsibilities
- Architect solutions covering data pipelines, feature engineering, model development, deployment, monitoring, and lifecycle management.
- Design secure, scalable architectures across AWS, Azure, GCP, and hybrid environments.
- Lead projects involving NLP, computer vision, forecasting, recommender systems, and generative AI.
- Enable GenAI and LLMOps adoption through fine-tuning, RAG, prompt engineering, and orchestration.
- Champion explainability, fairness, privacy, bias mitigation, and governance in AI delivery.
- Evaluate emerging technologies and recommend approaches tailored to client use cases.
Leadership and Consulting
- Lead and mentor cross-functional teams of data engineers, ML engineers, and consultants.
- Support proposals, client pitches, solution accelerators, and thought leadership.
- Coach junior consultants and foster continuous learning across the AI/ML practice.
Required Experience
- At least six years of experience implementing ML or AI models in production is required.
- At least three years of professional consulting or IT services experience with client-facing leadership is required.
- Deep ML/DL expertise and proficiency in GenAI frameworks are required.
- Strong programming skills in Python, R, or Scala and experience building scalable ML pipelines are required.
- Experience with cloud AI/ML services, big data ecosystems, MLOps or LLMOps, CI/CD, observability, and containerization is required.
- Strong understanding of AI architecture tradeoffs and ability to communicate with technical, non-technical, and executive stakeholders are required.
Workplace
- The role is hybrid, with onsite attendance expected when required by the team leader or client.
Compensation
- The expected base salary range is CAD 140,000 to CAD 170,000.
- A discretionary bonus of up to 12% may be available based on individual and company performance.
Benefits
- Benefits and perks include health and dental coverage, insurance, retirement matching, paid time off, wellness support, employee groups, and other eligibility-based programs.
Hiring Process
- Employment is subject to completion of a background check.
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