Autodesk
Intern, AI Data Developer (Winter)
Toronto, ON, CAN · Intern · Internship
Sponsorship not specifiedDetected 19 days ago
PythonGitSQLAWSAzureCloud PlatformsMachine Learningscikit-learnPandasSparkAirflowdbtData AnalysisData EngineeringData ScienceLLMsRAGAI OrchestrationStatisticsDesign SystemsExperimental DesignCommunicationCollaboration
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odds of building a lasting career here
38Risky
Cap-exempt (no lottery)0
Sponsors this role85
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 25 green-card filings in this occupation, 100% were for a worker who already held the job.
Green-card follow-through: 86%
Of 29 labor certifications old enough to have been used, 4 expired without the employer filing the next step. Median time from filing to decision: 483 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Reported a layoff in this occupation
In a green-card filing decided 2026-02-13, this employer stated it had laid off workers in Software Developers (CA) during the preceding six months.Describes the period before that filing, not necessarily today. Unlike WARN notices this is occupation-specific and federal.
Files H-1B transfers
12 transfer filings in the last year, covering 12 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- The work we do at Autodesk touches nearly every person on the planet.
- By creating software for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.
- Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies.
Responsibilities
- Design, build, and maintain data pipelines (ETL/ELT) that ingest, clean, validate, and transform large-scale telemetry and operational data
- Engineer features from raw signals to support scoring, classification, or ranking models, and iterate on model performance against benchmark datasets
- Build and maintain data models, schemas, and versioned datasets that other engineers and analysts can rely on
- Evaluate model and pipeline output for accuracy, drift, and reliability, and implement monitoring/alerting to catch regressions early
- Design, prototype, or build a proof-of-concept extension or integration end-to-end in collaboration with platform stakeholders
- Document data pipeline architecture, data contracts, and technical decisions to support handoff and future maintainability
- Solid understanding of data engineering fundamentals: ETL/ELT pipeline design, data validation, schema design, and dataset versioning
- As an AI Data Developer Intern on the Advanced Compliance Products (ACP) team at Autodesk, you will help build and scale the data pipelines, models, and platform integrations that power ACP's compliance and analytics capabilities.
- You will work alongside data engineers, AI/ML engineers, and platform teams to design systems that ingest and process large volumes of telemetry, engineer features for scoring and classification models, and extend shared internal platforms with new domain-specific capabilities; all while ensuring data quality, reliability, and observability throughout the pipeline.
Requirements
- Currently enrolled in a full-time undergraduate degree program with expected graduation of April 2027 or later
- Proficiency in Python and SQL, including data manipulation and ML libraries (e.g., pandas, Scikit-learn, PySpark)
- Experience with Git and familiarity with cloud environments and distributed data processing (e.g., AWS, Azure, Spark)
- Hands-on experience using AI coding assistants (e.g., Cursor, Claude Code, GitHub Copilot) to write, debug, or refactor code
Nice to have
- Experience with large-scale/distributed data processing frameworks (PySpark, Spark SQL) against production-scale data
- Experience with workflow orchestration and pipeline tooling (e.g., Airflow, dbt) and data warehousing concepts
- Exposure to classification/scoring models, anomaly detection, or feature engineering on structured/behavioral signals
- Familiarity with GenAI/LLM-powered platforms (e.g., internal chatbots, RAG-based BI tools) and their underlying architecture
- Experience reverse-engineering or "diffing" black-box system outputs against raw inputs to infer underlying logic
- Practical experience using AI tools (e.g., Cursor, Claude Code) for tasks beyond code generation such as codebase comprehension, test generation, documentation, and data analysis
- Strong written communication skills for producing architecture docs, data contracts, and stakeholder-facing recommendations
- Interest in compliance, licensing, or fraud/risk-detection domains
Compensation
- Salary transparency
Benefits
- Understanding of Machine Learning lifecycle workflows, model evaluation (precision/recall), and experimental design
Company info
- We take great pride in our culture here at Autodesk - it's at the core of everything we do.
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This listing is sourced directly from Autodesk's careers page and normalized into a canonical job model.