Software Engineer(AI/ML Platform)
Autodesk, Inc. (company site, opens in a new tab)2–5 yrsPuneOn-siteDirect career pageEst. 10–20 LPA
Posted 13h ago
Reach people at Autodesk, Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Autodesk, Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design and develop scalable AI/ML serving systems ensuring low latency and reliability across hybrid cloud environments.
- Architect and manage hybrid cloud infrastructure involving on-premises resources and multiple cloud providers to optimize performance and cost.
- Oversee AI/ML model deployment lifecycle including CI/CD pipelines, versioning, performance monitoring, and compliance.
- Collaborate with cross-functional teams to translate AI/ML research into production-ready systems.
Minimum Requirements
- Bachelor’s or Master’s degree in Computer Science or equivalent practical experience.
- 2 to 5 years of professional software development experience delivering production systems.
- Hands-on experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and Python programming.
- Experience in hybrid cloud system design and management with knowledge of Azure, containerization (Docker), orchestration (Kubernetes), and familiarity with DevOps practices (CI/CD).
Ideal Candidate Profile
- Experienced in architecting scalable AI/ML serving platforms in hybrid cloud environments.
- Strong background in integrating AI/ML model lifecycle management with cloud infrastructure and DevOps.
- Comfortable working with cross-functional teams including AI/ML researchers and data engineers to operationalize ML models.