Senior Machine Learning and AI Engineer

Autodesk Autodesk · Enterprise · Toronto, ON +1

Senior Machine Learning & AI Engineer to build foundation of intelligence-driven user management and access systems. This role will define and deliver ML capabilities from the ground up, leading development of intelligent systems for proactive automation, predictions, and recommendations. Responsibilities include end-to-end ML system development, data pipelines, model development for prediction/recommendation/anomaly detection, real-time/batch inference systems, and collaboration with platform/experience engineering teams.

What you'd actually do

  1. Lead the end-to-end development of ML/AI systems, from problem definition and data strategy to model development and production deployment
  2. Design and build scalable data pipelines by integrating with existing platforms and establishing new data sources where needed
  3. Develop and deploy machine learning models for prediction, recommendation, and anomaly detection in user management and access workflows
  4. Build and integrate real-time and batch inference systems into APIs, microservices, and user-facing applications
  5. Work at the intersection of machine learning, platform engineering, and distributed systems to deliver robust, scalable solutions

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Pandas
  • XGBoost
  • designing data pipelines
  • large-scale or distributed data systems
  • building APIs
  • distributed systems
  • AWS
  • GCP
  • Azure
  • S3
  • Lambda
  • ECS
  • Step Functions
  • event-driven architectures
  • CDC
  • SQS
  • SNS
  • interpersonal and communication skills
  • collaborate effectively across teams
  • agile environment
  • operate independently
  • drive projects from concept to delivery in ambiguous environments

Nice to have

  • Machine Learning
  • applied AI

What the JD emphasized

  • greenfield
  • high-impact role
  • define and deliver machine learning capabilities from the ground up
  • early ML hire
  • high ownership
  • shaping everything from data strategy and pipelines to model development and production systems
  • Drive projects independently in ambiguous environments
  • taking ownership from concept through delivery

Other signals

  • end-to-end development of ML/AI systems
  • define and deliver machine learning capabilities from the ground up
  • operate with high ownership
  • shaping everything from data strategy and pipelines to model development and production systems