Autodesk

SeniorMachineLearningandAIEngineer

Toronto, Ontario, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning and AI Engineer at Autodesk. Skills: Machine Learning, AI, Platform engineering, Distributed systems. Lead end-to-end development of ML/AI systems. Define problem”

Industry & Context.

Problems you'll solve

Root cause analysis

What They're Looking For.

Must Have

Bachelor's degree in Computer Science, Machine Learning, Applied Mathematics, or a related field (or equivalent practical experience), 3+ years of experience in Machine Learning, applied AI, or related fields, Proven experience building and deploying ML systems in production environments, Proficiency in Python and common ML libraries/frameworks such as PyTorch, TensorFlow, scikit-learn, Pandas, or XGBoost, Experience designing data pipelines and working with large-scale or distributed data systems, Solid software engineering skills, including experience building APIs and working with distributed systems, Experience building and deploying systems on AWS (or similar cloud platforms such as GCP or Azure), including familiarity with services such as S3, Lambda, ECS, or Step Functions, Familiarity with event-driven architectures and tools (CDC, SQS, SNS)

What You'll Do.

Lead end-to-end development of ML/AI systems

Develop data strategy

Design scalable data pipelines

Integrate with existing platforms

Establish new data sources

Develop ML models for prediction

Develop ML models for recommendation

Develop ML models for anomaly detection

Build inference systems

Integrate inference systems into APIs

Integrate inference systems into microservices

Integrate inference systems into user-facing applications

Work at intersection of ML

Deliver robust solutions

Deliver scalable solutions

Collaborate with platform engineering teams

Collaborate with experience engineering teams

Define service architecture

Define event-driven systems

Establish best practices for ML development

Establish best practices for ML experimentation

Establish best practices for ML deployment

Establish best practices for ML monitoring

Drive projects independently

Operate in ambiguous environments

Take ownership from concept through delivery

Collaborate effectively across teams

Contribute to best practices

Contribute to high technical standards

How You'll Work.

Team & Collaboration

Platform engineering teams; Experience engineering teams; Cross-functional teams

Communication Scope

Interpersonal skills; Communication skills

Process & Methodology

Agile environment

Full Job Description

**Job Requisition ID #** 26WD96898 **Position Overview** Autodesk is looking for a Senior Machine Learning & AI Engineer to help build the foundation of intelligence-driven user management and access systems within our Admin Access & Insights organization. This is a greenfield, high-impact role where you will define and deliver machine learning capabilities from the ground up. You will lead the development of intelligent systems that shift our platform from reactive workflows to proactive automation, predictions, and recommendations around user administration and access. As an early ML hire in this space, you will operate with high ownership - shaping everything from data strategy and pipelines to model development and production systems, working at the intersection of machine learning, platform engineering, and large-scale distributed systems. **Responsibilities** * Lead the end-to-end development of ML/AI systems, from problem definition and data strategy to model development and production deployment * Design and build scalable data pipelines by integrating with existing platforms and establishing new data sources where needed * Develop and deploy machine learning models for prediction, recommendation, and anomaly detection in user management and access workflows * Build and integrate real-time and batch inference systems into APIs, microservices, and user-facing applications * Work at the intersection of machine learning, platform engineering, and distributed systems to deliver robust, scalable solutions * Collaborate closely with platform and experience engineering teams on service architecture, APIs, and event-driven systems * Establish best practices for ML development, experimentation, deployment, and monitoring * Drive projects independently in ambiguous environments, taking ownership from concept through delivery * Collaborate effectively across teams, sharing knowledge and contributing to best practices and high technical standards **Minimum Qualification

Free ATS check

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