Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- MLOps Developer optimizing AI-powered applications and collaborating within a hybrid-remote team at Autodesk. Focused on automation, infrastructure, and enhancing AI solutions.
Responsibilities
- Improve team efficiency through MLOps and DevOps best practices
- Develop, maintain, and ensure reliability of inference services
- Adapt retrieval models to automated deployment pipelines
- Collaborate to enable scaling of training and inference
- Monitor model performance and overall platform efficiency
- Evolve single-version codebases into iterative solutions
- Contribute to governance and security practices
- Identify opportunities for automation and process optimization
- Collaborate to ensure adherence to service-level agreements (SLAs)
Requirements
- 3 to 5 years of hands-on experience in MLOps / DevOps in a production environment
- Experience with cloud platforms such as AWS or Azure
- Proficient in Infrastructure as Code practices using Terraform
- Expertise in containerization technologies (Docker, Kubernetes)
- Experience implementing CI/CD pipelines for machine learning projects
- Experience building reliable and scalable inference APIs (Flask, FastAPI)
- Understanding of security best practices in MLOps
Benefits
- Annual cash bonuses
- Equity grants
- Comprehensive benefits package
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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