Design and make software for architecture, engineering, construction, and entertainment industries.
Lead design & development of Autodesk Insights AI platform, ensuring scalable, reliable services.
3 days ago ago
Expert & Leadership (13+ years)
Full Time
Toronto, Ontario, Canada
Office Full-Time
Company Size
11,600 Employees
Service Specialisms
Design
Engineering
Construction
Architecture
Consulting
Product Development
Technology Solutions
Software Development
Sector Specialisms
Building Design
Construction
Automotive
Building Product Manufacturing
3D Animation
Architecture
Engineering
Construction Professionals
Role
Description
automation
architecture
inference
data management
collaboration
system design
Automate & Streamline: Identify opportunities to simplify and automate workflows, from data processing to deployment.
Architectural Ownership: Provide technical leadership and set architectural direction for critical components of the Insights platform.
Inference at Scale: Design and implement low-latency, high-throughput prediction and inference services.
Data & Big Data Management: Orchestrate and automate large-scale data transformations, pipelines, and artifact storage.
Cross-Team Collaboration: Partner with researchers, product managers, architects, and engineers across domains to align solutions with business and customer needs.
Architect & Lead: Drive the design and development of core systems for Autodesk’s Insights platform, ensuring scalability, reliability, and performance.
Requirements
python
aws
spark
msc
distributed
communication
Excellent communication, presentation, and interpersonal skills.
Expertise in programming (Python, Java, Go, SQL, scripting languages).
8+ years in software development with proven delivery of production-grade systems and services.
Strong record in distributed system design and scalable software architecture.
Excellent critical reasoning and decision-making skills.
Hands-on experience with AWS or Azure cloud technologies.
Possessing an understanding of statistical analysis and prior collaboration with data scientists or researchers.
Experience building and optimizing data platforms (storage, retrieval, processing).
MS in Computer Science or equivalent practical experience.
Proficiency with big data platforms (Hadoop, Spark, Hive, NoSQL, pipelines).