ML Ops Developer, Fusion
Autodesk
ML Ops Developer, Fusion
Job Description
ML Ops Developer, Fusion
📋 Job Overview
The ML Ops Developer role at Autodesk for Fusion involves building and maintaining machine learning operations infrastructure to support AI-driven features in the Fusion product suite. The position focuses on deploying, monitoring, and scaling ML models in cloud environments across multiple locations. This role requires expertise in DevOps practices tailored to machine learning workflows.
📍 Location: 3 Locations, 3 Locations
📅 Posted: Posted 16 Days Ago
🎯 Key Responsibilities
- Design and implement CI/CD pipelines for ML models
- Collaborate with data scientists to optimize model training and deployment
- Monitor and troubleshoot ML systems in production environments
- Ensure scalability and reliability of AI features in Fusion applications
- Document processes and mentor junior team members
✅ Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- 3+ years of experience in software development or DevOps
- Experience with machine learning pipelines and model deployment
- Proficiency in cloud platforms such as AWS, Azure, or GCP
⭐ Preferred Qualifications
- Master's degree in AI, Machine Learning, or related discipline
- Experience with Autodesk products or CAD/CAM software
- Knowledge of MLOps tools like Kubeflow or MLflow
- Contributions to open-source ML projects
🛠️ Required Skills
- Python programming
- Docker and Kubernetes for containerization
- CI/CD tools (Jenkins, GitLab CI)
- Cloud services (AWS SageMaker, Azure ML)
- Version control with Git
- Monitoring tools (Prometheus, Grafana)
- Agile methodologies and collaboration skills
🎁 Benefits & Perks
- Comprehensive health, dental, and vision insurance
- 401(k) matching and retirement plans
- Flexible work arrangements and remote options
- Professional development budget and tuition reimbursement
- Paid time off, parental leave, and wellness programs
Locations
- 3 Locations, 3 Locations
Salary
Skills Required
- Python programmingintermediate
- Docker and Kubernetes for containerizationintermediate
- CI/CD tools (Jenkins, GitLab CI)intermediate
- Cloud services (AWS SageMaker, Azure ML)intermediate
- Version control with Gitintermediate
- Monitoring tools (Prometheus, Grafana)intermediate
- Agile methodologies and collaboration skillsintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field (experience)
- 3+ years of experience in software development or DevOps (experience)
- Experience with machine learning pipelines and model deployment (experience)
- Proficiency in cloud platforms such as AWS, Azure, or GCP (experience)
Preferred Qualifications
- Master's degree in AI, Machine Learning, or related discipline (experience)
- Experience with Autodesk products or CAD/CAM software (experience)
- Knowledge of MLOps tools like Kubeflow or MLflow (experience)
- Contributions to open-source ML projects (experience)
Responsibilities
- Design and implement CI/CD pipelines for ML models
- Collaborate with data scientists to optimize model training and deployment
- Monitor and troubleshoot ML systems in production environments
- Ensure scalability and reliability of AI features in Fusion applications
- Document processes and mentor junior team members
Benefits
- general: Comprehensive health, dental, and vision insurance
- general: 401(k) matching and retirement plans
- general: Flexible work arrangements and remote options
- general: Professional development budget and tuition reimbursement
- general: Paid time off, parental leave, and wellness programs
Tags & Categories
Answer 10 quick questions to check your fit for ML Ops Developer, Fusion @ Autodesk.
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ML Ops Developer, Fusion
Autodesk
ML Ops Developer, Fusion
Job Description
ML Ops Developer, Fusion
📋 Job Overview
The ML Ops Developer role at Autodesk for Fusion involves building and maintaining machine learning operations infrastructure to support AI-driven features in the Fusion product suite. The position focuses on deploying, monitoring, and scaling ML models in cloud environments across multiple locations. This role requires expertise in DevOps practices tailored to machine learning workflows.
📍 Location: 3 Locations, 3 Locations
📅 Posted: Posted 16 Days Ago
🎯 Key Responsibilities
- Design and implement CI/CD pipelines for ML models
- Collaborate with data scientists to optimize model training and deployment
- Monitor and troubleshoot ML systems in production environments
- Ensure scalability and reliability of AI features in Fusion applications
- Document processes and mentor junior team members
✅ Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- 3+ years of experience in software development or DevOps
- Experience with machine learning pipelines and model deployment
- Proficiency in cloud platforms such as AWS, Azure, or GCP
⭐ Preferred Qualifications
- Master's degree in AI, Machine Learning, or related discipline
- Experience with Autodesk products or CAD/CAM software
- Knowledge of MLOps tools like Kubeflow or MLflow
- Contributions to open-source ML projects
🛠️ Required Skills
- Python programming
- Docker and Kubernetes for containerization
- CI/CD tools (Jenkins, GitLab CI)
- Cloud services (AWS SageMaker, Azure ML)
- Version control with Git
- Monitoring tools (Prometheus, Grafana)
- Agile methodologies and collaboration skills
🎁 Benefits & Perks
- Comprehensive health, dental, and vision insurance
- 401(k) matching and retirement plans
- Flexible work arrangements and remote options
- Professional development budget and tuition reimbursement
- Paid time off, parental leave, and wellness programs
Locations
- 3 Locations, 3 Locations
Salary
Skills Required
- Python programmingintermediate
- Docker and Kubernetes for containerizationintermediate
- CI/CD tools (Jenkins, GitLab CI)intermediate
- Cloud services (AWS SageMaker, Azure ML)intermediate
- Version control with Gitintermediate
- Monitoring tools (Prometheus, Grafana)intermediate
- Agile methodologies and collaboration skillsintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field (experience)
- 3+ years of experience in software development or DevOps (experience)
- Experience with machine learning pipelines and model deployment (experience)
- Proficiency in cloud platforms such as AWS, Azure, or GCP (experience)
Preferred Qualifications
- Master's degree in AI, Machine Learning, or related discipline (experience)
- Experience with Autodesk products or CAD/CAM software (experience)
- Knowledge of MLOps tools like Kubeflow or MLflow (experience)
- Contributions to open-source ML projects (experience)
Responsibilities
- Design and implement CI/CD pipelines for ML models
- Collaborate with data scientists to optimize model training and deployment
- Monitor and troubleshoot ML systems in production environments
- Ensure scalability and reliability of AI features in Fusion applications
- Document processes and mentor junior team members
Benefits
- general: Comprehensive health, dental, and vision insurance
- general: 401(k) matching and retirement plans
- general: Flexible work arrangements and remote options
- general: Professional development budget and tuition reimbursement
- general: Paid time off, parental leave, and wellness programs
Tags & Categories
Answer 10 quick questions to check your fit for ML Ops Developer, Fusion @ Autodesk.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs