Senior Consultant, ML/AI Engineer, Data & AI

Toast; Vancouver; On-site; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Total rewards program

Career development

Job summary

Toast is partnering with a global professional services firm to recruit a Senior Consultant, ML/AI Engineer in Vancouver. You will apply advanced analytics, ML and GenAI to deliver secure, production-ready solutions across on-prem and cloud environments with a focus on Azure, alongside GCP and AWS.

You will work hands-on in a client-facing role to translate business requirements into end-to-end ML/AI designs, build and deploy models, and implement MLOps pipelines while upholding responsible AI

Qualifications

• University degree in computer science, engineering, data science, mathematics, or a related field.
• 3+ years of professional experience in machine learning, data science, AI engineering, or a related field, with a track record of delivering production ML solutions.
• Strong Python skills for data analysis, machine learning, and model development.
• Hands-on experience with ML frameworks and platform tools such as scikit-learn, TensorFlow, PyTorch, Azure ML Studio, and Databricks MLflow.
• Solid understanding of ML algorithms, statistics, model evaluation, and feature engineering.
• Experience designing and building end-to-end ML pipelines, from data preprocessing and training through validation, deployment, and monitoring.
• Practical MLOps experience including CI/CD, model versioning, experiment tracking, and automated retraining.
• Experience deploying ML models to Azure, AWS, or GCP with an understanding of cloud-native architecture and security principles.
• Experience with generative AI, LLMs, prompt engineering, or retrieval-augmented generation (RAG).
• Strong consulting and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Proven ability to collaborate within cross-functional, multi-disciplinary teams.

Responsibilities

• Partner with clients to understand their business problems and identify where AI and advanced analytics can make an impact.
• Translate business and analytical requirements into end-to-end ML/AI solution designs.
• Carry out ML/AI engineering work including exploratory data analysis, data preparation, and model development (forecasting, classification, recommendation, anomaly detection) using Python and frameworks such as scikit-learn, TensorFlow, PyTorch, Azure ML Studio, and Databricks MLflow.
• Build and optimize AI and GenAI solutions using platforms such as AI Foundry, GCP Vertex AI, AWS SageMaker, and Bedrock.
• Operationalize AI/ML pipelines using MLOps best practices, including model deployment, versioning, CI/CD, automated testing, and monitoring.
• Implement model monitoring, performance tuning, drift detection, and retraining strategies in production.
• Work with data engineers to ensure reliable, scalable data pipelines that support model training and inference.
• Apply responsible AI principles including explainability, bias detection, model governance, and security and privacy compliance.
• Support client workshops, technical discussions, and stakeholder presentations on AI strategy, solution design, and implementation.

Skills

Python

ML engineering

MLOps

Cloud deployment

Data pipelines

Explainable AI

Client communication

Team collaboration

AI governance

Education

Bachelor’s degree in Computer Science

Tools

scikit-learn

TensorFlow

PyTorch

Azure ML Studio

Databricks MLflow

Job description

Job Description

Toast is recruiting on behalf of a global professional services firm with a large Canadian presence and thousands of professionals across the country, for a Senior Consultant, ML/AI Engineer to join its Data & AI practice in Vancouver. The firm helps some of Canada’s largest organizations solve complex business challenges, and its Data & AI team builds and scales machine learning and generative AI solutions for clients across industries. In this hands-on, client-facing role, you will turn advanced analytics, ML, and GenAI use cases into secure, production-ready solutions across on-prem and cloud environments, with a focus on Azure alongside GCP and AWS.

Responsibilities

• Partner with clients to understand their business problems and identify where AI and advanced analytics can make an impact
• Translate business and analytical requirements into end-to-end ML/AI solution designs
• Carry out ML/AI engineering work including exploratory data analysis, data preparation, and model development (forecasting, classification, recommendation, anomaly detection) using Python and frameworks such as scikit-learn, TensorFlow, PyTorch, Azure ML Studio, and Databricks MLflow
• Build and optimize AI and GenAI solutions using platforms such as AI Foundry, GCP Vertex AI, AWS SageMaker, and Bedrock
• Operationalize AI/ML pipelines using MLOps best practices, including model deployment, versioning, CI/CD, automated testing, and monitoring
• Implement model monitoring, performance tuning, drift detection, and retraining strategies in production
• Work with data engineers to ensure reliable, scalable data pipelines that support model training and inference
• Apply responsible AI principles including explainability, bias detection, model governance, and security and privacy compliance
• Support client workshops, technical discussions, and stakeholder presentations on AI strategy, solution design, and implementation

Requirements

• University degree in computer science, engineering, data science, mathematics, or a related field
• 3+ years of professional experience in machine learning, data science, AI engineering, or a related field, with a track record of delivering production ML solutions
• Strong Python skills for data analysis, machine learning, and model development
• Hands-on experience with ML frameworks and platform tools such as scikit-learn, TensorFlow, PyTorch, Azure ML Studio, and Databricks MLflow
• Solid understanding of ML algorithms, statistics, model evaluation, and feature engineering
• Experience designing and building end-to-end ML pipelines, from data preprocessing and training through validation, deployment, and monitoring
• Practical MLOps experience including CI/CD, model versioning, experiment tracking, and automated retraining
• Experience deploying ML models to Azure, AWS, or GCP with an understanding of cloud-native architecture and security principles
• Experience with generative AI, LLMs, prompt engineering, or retrieval-augmented generation (RAG)
• Strong consulting and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders
• Proven ability to collaborate within cross-functional, multi-disciplinary teams

Nice to haves

• Familiarity with big data or distributed processing frameworks such as Spark is considered an asset
• Experience fine-tuning foundational models would be a plus
• Cloud AI/ML certifications such as Azure AI Engineer Associate, AWS Machine Learning Specialty, Google Professional ML Engineer, Databricks ML Engineer Associate, or Databricks Generative AI Engineer would be a plus

Benefits

• Compensation listed on the posting is for base salary. Total compensations includes base salary + annual bonuses.
• A comprehensive total rewards program covering health, wellness, and career support
• Put AI into production for some of Canada’s largest organizations, with your models shaping real decisions in forecasting, risk, and customer experience
• Build hands-on depth across all three major clouds (Azure, GCP, AWS) and the latest GenAI platforms in a single role
• Help set the standard for responsible AI in Canada by building explainability, bias detection, and governance into every solution you ship
• Grow your career inside a firm that supports learning at every stage, with room to move from engineering into AI strategy and client leadership