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Senior AI Engineer – AI Platform, ML Engineering
Aviso Wealth. Build reusable AI and ML engineering patterns that help teams move from proof-of-value to production safely and consistently .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying AI and ML solutions with a strong focus on MLOps and LLMOps practices. Proficient in utilizing cloud platforms like AWS and Databricks for model deployment, monitoring, and governance.
Highest-signal resume keywords
MLOps PracticesDatabricks CertificationAWS CertificationPython Development SkillsModel Evaluation and Monitoring
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningAI EngineeringData EngineeringModel DeploymentModel ServingFeature EngineeringAPI IntegrationCloud EngineeringAutomationTesting
Soft Skills
Consultative SkillsCommunication Skills
Tools & Technologies
AWSDatabricksMLflowAzureLakehouse Platforms
Certifications & Qualifications
Databricks CertificationAWS CertificationsMicrosoft Azure CertificationsMLOps CertificationLLMOps Certification
Industry Keywords
AI GovernanceData ProductsOperational RiskEnterprise SecurityProduction Workflows
Tech Stack
Tools & technologiesAWSAzureCloudPython
About the role
Key responsibilities & impact- Build reusable AI and ML engineering patterns that help teams move from proof-of-value to production safely and consistently
- Establish practical MLOps and LLMOps practices using Databricks, AWS, MLflow and related platform capabilities
- Create standards and templates for model deployment, serving, monitoring, evaluation, and production release
- Support API integration and deployment patterns for ML, GenAI and agentic solutions
- Partner with Data Engineering and Data Management to define feature engineering data products and reusable pipeline patterns
- Define versioning, tracking, monitoring, and governance for models, prompts, agents, data products, and AI outputs
- Partner with Data and AI Governance to embed responsible AI, lineage, access control, auditability, and risk controls into production workflows
- Monitor AI cost, performance, reliability, usage, and operational risk
- Contribute to reusable standards and community learning
- Report to the Sr. Director of Data Science and AI Enablement
Requirements
What you’ll need- Bachelor’s or Master's Degree in Computer Science, Software Engineering, Data Engineering, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Engineering or related technical field
- Equivalent hands-on experience building data, AI, machine learning, platform, or cloud engineering solutions may be considered in place of formal education
- 10+ years of overall experience
- 4+ years of experience building, deploying, or supporting machine learning, AI, or data-driven solutions in production environments
- 5 to 7 years working in the data space
- Databricks certification related to Machine Learning, Data Engineering, Generative AI or platform administration
- AWS certifications related to cloud architecture, machine learning, AI, DevOps, data engineering or security
- Microsoft Azure certifications related to AI, data, cloud engineering, DevOps, or security
- Other relevant certifications in MLOps, LLMOps, cloud platforms, DevOps, security, architecture, or enterprise AI platforms
- Strong Python development skills for ML engineering, automation, APIs, testing and production implementation
- Hands-on experience with cloud-based AI/ML platforms, AWS, Databricks, Azure, MLflow or Lakehouse platforms
- Strong understanding of MLOps, CI/CD/CT, model deployment, model serving, and production release practices
- Experience with model evaluation, validation, monitoring and observability
- Familiarity with LLMOps practices for GenAI and agentic solutions in production
- Experience developing reusable AI/ML platform patterns
- Understanding of enterprise security, governance, and control requirements for production AI and ML workloads
- Strong consultative and communication skills
- Fluent communication skills in English required; bilingual French is an asset
Benefits
Comp & perks- Competitive compensation package that rewards and recognizes individual contributions
- Excellent health, dental and insurance benefits
- Generous vacation time
- Fitness benefit
- Parental leave top-up options
- Matching contributions to the retirement program
- Learning and development opportunities
- Education assistance program
- Regular social events