Data Scientist

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, 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.

Autodesk is transforming the way the world designs, builds, and innovates through AI and data-driven insights. As a Data Scientist, you will leverage advanced machine learning, statistical modeling, and data analytics to solve complex challenges across Autodesk’s products and services. You will work with cross-functional teams to develop scalable AI/ML solutions, optimize decision-making, and enhance user experiences.

• Develop AI/ML models and solutions over a large-scale data that address business problems and drive product innovation

• Develop & deploy end-to-end AI/ML pipelines, from data ingestion and preprocessing to model training, validation, deployment, and monitoring

• Conduct A/B testing, experiment design, and hypothesis testing to evaluate product and feature performance

• Apply AI/ML based algorithms to build classic data science applications like personalization, recommendation systems etc. by solving complex business problem statements

• 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

• Optimize workflows and scripts on data lake for data cleaning, processing, and transformation

• Master's degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent work experience

• 3+ years of experience in data science, machine learning, or AI, with a proven track record of delivering successful AI-driven solutions at scale

• Expertise in developing and deploying machine learning models, particularly in large-scale environments, with a focus on deep learning, reinforcement learning, or natural language processing

• Strong proficiency in programming languages such as Python, with experience in using machine learning libraries such as, Py Torch

• Deep knowledge of data engineering, statistical analysis, and data visualization techniques

• Experience with cloud-based AI/ML platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Hadoop, Spark)

• Hands-on expertise in AI and LLM development in a real-world business environment

• Hands-on experience with various statistical and machine learning techniques including classification, regression, dimension reduction, regularization, clustering and various multivariate methods

• Proficient with relational data modeling and SQL & Snowflake or comparable Data Warehouse and ETL tooling like Astronomer/Airflow and DBT

• Proficient working in an AWS environment and leveraging its offerings such as EC2, S3, Lambda, Glue, Athena, Sage Maker etc.

• Strong publication record in top-tier AI/ML conferences or journals

• Experience deploying AI models for real-time applications in manufacturing or construction

• Strong programming skills in Python & associated libraries for AI/ML

• Strong programming experience in LLM application development

• Proficient with fine-tuning large language models

• Strong knowledge base of MLOps practices for efficient model deployment and scaling

• Strong communication skills and the ability to convey technical concepts to non-technical audiences

• Proficient with version control (Git/Git Hub) and working in collaborative coding…