Job Requisition ID #

24WD82800

Position Overview

Autodesk customers make sense of the world through rich streams of data that might include 3D scans of buildings, fluid dynamic simulations, daily notes on the construction site, trends on product usage and more. As a Data Scientist Intern, you will get to apply your knowledge in AI, Data engineering, work with the latest Machine learning models, contribute to the next generation applied AI applications and make an impact by helping our customers create a better, safer, more sustainable world.

Responsibilities

• Apply AI/ML models over large-scale data to uncover key business trends and opportunities.
• Translate insights into actionable recommendations, effectively guiding business strategy through clear communication with cross-functional teams.
• Apply AI/ML based algorithms to build classic data science applications like personalization, recommendation systems etc.
• Develop, prototype, and deploy large language models by leveraging large scale using AWS Cloud Services.
• Develop applied AI/ML based applications that integrate data from a wide variety of sources such as relational databases, AWS, data virtualization tools
• Analyze and preprocess large datasets for model development, including data cleaning, feature engineering, and exploratory data analysis (EDA).
• Optimize the efficiency, scalability, and robustness of deployed AI/ML models, ensuring they perform reliably & cost efficiency under various conditions and can handle growing data demands.
• Understand technology operations data from many different sources in detail to create these models
• Optimize workflows and scripts on data lake for data cleaning, processing, and transformation
• Extract and derive useful metrics and KPIs from raw data gathered from multiple data sources

• Pursuing a master's in computer science or data science in Canada.
• Hands-on experience in AI and LLM development in a real-world business environment.
• Familiarity with various statistical and machine learning techniques including classification, regression, dimension reduction, regularization, clustering and various multivariate methods
• Familiarity with relational data modeling and SQL
• Familiarity with Snowflake or comparable Data Warehouse and ETL tooling like Astronomer/Airflow and DBT.
• Experience working in an AWS environment and leveraging its offerings such as EC2, S3, Lambda, Glue, Athena, SageMaker etc.
• Strong programming skills in Python & associated libraries for AI/ML
• Strong programming experience in LLM application development

• Experience with fine-tuning large language models
• Knowledge of MLOps practices for efficient model deployment and scaling.
• Strong communication skills and the ability to convey technical concepts to non-technical audiences.
• Experience with version control (Git/GitHub) and working in collaborative coding environments.
• Be self-motivated, creative and collaborative