Senior Production ML Engineer: Scalable AI Pipelines

Autodesk; Canada; On-site; CAD 123,000 - 180,000; Full time

Job summary

Autodesk is seeking a Machine Learning Engineer to design, build, and operationalize production-grade ML and AI systems for the Go-to-market intelligence function. You will collaborate with data teams and stakeholders to deliver scalable data products, focusing on observability, governance, and cost efficiency.

The role emphasizes end-to-end ML pipelines, model evaluation frameworks, and production deployment with strong engineering discipline.

Qualifications

• Bachelor's degree in a technical field.
• 5+ years of ML engineering or data engineering experience including production systems.
• Experience designing and operating production ML systems.
• Strong Python programming skills for production software.
• Experience with Snowflake and Snowflake cost optimization.
• Experience with Airflow or similar orchestration frameworks.
• DBT data transformation experience.
• Hands-on building ML inference pipelines and services.
• Experience deploying workloads to AWS.
• Git-based workflows and collaborative engineering.
• Familiarity with MLOps concepts and model lifecycle.
• Experience with structured and unstructured data pipelines.
• Strong analytical, debugging and communication skills.
• Ability to work with distributed teams across time zones.
• Familiarity with Agile/Scrum.

Responsibilities

• Design, develop, test, deploy, and maintain production-grade ML pipelines.
• Develop reusable ML services and components.
• Develop robust model evaluation frameworks covering accuracy, relevance, groundedness, consistency, latency, throughput, robustness, and cost.
• Design automated evaluation pipelines using deterministic metrics and regression testing.
• Build and maintain distributed processing pipelines for large volumes of data.
• Design and optimize distributed pipeline and cloud orchestration for large-scale AI workloads.
• Implement resilient processing patterns including retries, checkpointing, and idempotent processing.
• Optimize AI/ML systems for latency, throughput, and cost.
• Partner with platform teams to integrate AI apps with APIs, IAM, monitoring and deployment infra.
• Implement MLOps practices including versioning, experiment tracking, and deployment automation.
• Build observability and monitoring across ML pipelines for health and cost.
• Identify and manage model drift and data drift.
• Develop modular frameworks and reusable components for self-service capabilities.
• Collaborate with data scientists, data engineers, analysts, product teams and stakeholders.
• Translate ML designs and trade-offs for technical and non-technical audiences.
• Support experimentation and rapid prototyping while ensuring production readiness.
• Contribute to engineering standards and architecture reviews.

Skills

Python

Production ML systems

Git-based workflows

Agile/Scrum

Remote time zones

Education

Bachelor's degree in a technical field

Tools

Airflow

DBT

Snowflake

Snow SQL

Snow Pipe

AWS

Git

MLOps

Job description

Autodesk is seeking a Machine Learning Engineer to design, build, and operationalize production-grade ML and AI systems for the Go-to-market intelligence function. You will collaborate with data teams and stakeholders to deliver scalable data products, focusing on observability, governance, and cost efficiency.

The role emphasizes end-to-end ML pipelines, model evaluation frameworks, and production deployment with strong engineering discipline.