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.
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.
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
Investigate how existing shared platforms and services are structured, identify coupling points and separation-of-concerns gaps, and propose or prototype ways to extend those platforms for new use cases
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
Present findings, benchmarks, and recommendations to engineering and business stakeholders
Minimum Qualifications
Currently enrolled in a full-time undergraduate degree program with expected graduation of April 2027 or later
Major in Computer Science, Engineering, Data Science, Statistics, or a related field
Proficiency in Python and SQL, including data manipulation and ML libraries (e.g., pandas, Scikit-learn, PySpark)
Solid understanding of data engineering fundamentals: ETL/ELT pipeline design, data validation, schema design, and dataset versioning
Understanding of Machine Learning lifecycle workflows, model evaluation (precision/recall), and experimental design
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
Comfortable working with ambiguous, outcome-based problems rather than a fixed task list
Preferred Qualifications
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
Understanding of platform/service architecture and separation-of-concerns design in a multi-tenant shared codebase
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
How You'll Use AI to Accelerate This Work
This internship is explicitly outcome-focused, not task-based. You are expected to use AI tools to move faster and go deeper, not just to execute a checklist:
Use AI coding assistants (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate pipeline development, feature engineering, and codebase comprehension when working in existing platforms
Apply ML methods and AI-assisted analysis to model scoring/classification signals and to diff system outputs against raw inputs, inferring underlying logic
Use AI-assisted documentation to produce architecture notes, data contracts, onboarding material, and workflow summaries as you go, rather than writing them from scratch at the end
Use AI-assisted analysis to map requirements against existing platform capabilities and quickly surface data quality or architectural gaps
Be prepared to explain and justify AI-assisted outputs (model choices, code, documentation) to your mentor and technical stakeholders. AI accelerates the work, but you own the judgment behind it
What You'll Gain
Hands-on experience building production-grade data pipelines and models that support real business decisions
Exposure to platform architecture, ownership, and contribution models within a large shared internal system
A portfolio of measurable outcomes: benchmarked models and pipelines with quantified impact, and a reusable technical playbook
About the Canada Intern Program
The 2027 Canada Internship program runs for 16 weeks (Jan 4 - April 23 2027). All internships are paid. As an intern, you will contribute to meaningful projects, be mentored by industry leaders, and participate in tech talks and other activities designed to support your personal and professional development. Our internships align with Autodesk's Flexible Workplace approach, which is designed to meet the needs of our business while providing flexibility in support of office, remote and hybrid work preferences.
About Autodesk
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary transparency
Salary is one part of Autodesk's competitive compensation package. Offers are based on the candidate's experience, educational level, and geographic location.
Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
In-Person Onboarding and Identity Verification
This role may require in-person onboarding and/or in-person ID verification.
From Autodesk's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.
