Autodesk
SeniorMachineLearningandAIEngineer
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“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.
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
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