Principal Machine Learning Operations Engineer
Autodesk
Principal Machine Learning Operations Engineer
Job Description
Principal Machine Learning Operations Engineer
📋 Job Overview
The Principal Machine Learning Operations Engineer at Autodesk leads the design, development, and deployment of scalable MLOps infrastructure to support machine learning initiatives. This role involves collaborating with data scientists and engineers to operationalize ML models, ensuring reliability, efficiency, and integration with Autodesk's cloud platforms. The position focuses on advancing AI capabilities in design and engineering software products.
📍 Location: Bengaluru
📅 Posted: Posted 30+ Days Ago
🎯 Key Responsibilities
- Design and implement MLOps frameworks for end-to-end ML workflows
- Collaborate with cross-functional teams to integrate ML models into Autodesk applications
- Optimize infrastructure for ML training and inference on cloud and on-premises systems
- Monitor and troubleshoot ML systems for performance and reliability
- Drive best practices in CI/CD for machine learning and mentor junior engineers
✅ Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or related field
- 8+ years of experience in machine learning operations or DevOps with a focus on ML
- Proven track record of deploying ML models at scale in production environments
- Strong understanding of ML pipelines, model monitoring, and lifecycle management
⭐ Preferred Qualifications
- Experience with Autodesk products or AEC industry
- PhD in a relevant field
- Contributions to open-source MLOps projects
- Familiarity with federated learning or edge ML deployment
🛠️ Required Skills
- Proficiency in Python, Java, or Scala for ML engineering
- Expertise in ML frameworks like TensorFlow, PyTorch, or scikit-learn
- Experience with Kubernetes, Docker, and container orchestration
- Knowledge of cloud platforms such as AWS, Azure, or GCP
- Skills in CI/CD tools like Jenkins, GitLab CI, or Kubeflow
- Strong problem-solving and communication skills
- Familiarity with data versioning tools like DVC and monitoring with Prometheus
🎁 Benefits & Perks
- Competitive salary and performance bonuses
- Comprehensive health, dental, and vision insurance
- 401(k) matching and retirement plans
- Flexible work arrangements and remote options
- Professional development opportunities and tuition reimbursement
- Employee stock purchase plan and wellness programs
Locations
- Bengaluru, India
Salary
Estimated Salary Rangemedium confidence
3,500,000 - 5,500,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python, Java, or Scala for ML engineeringintermediate
- Expertise in ML frameworks like TensorFlow, PyTorch, or scikit-learnintermediate
- Experience with Kubernetes, Docker, and container orchestrationintermediate
- Knowledge of cloud platforms such as AWS, Azure, or GCPintermediate
- Skills in CI/CD tools like Jenkins, GitLab CI, or Kubeflowintermediate
- Strong problem-solving and communication skillsintermediate
- Familiarity with data versioning tools like DVC and monitoring with Prometheusintermediate
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or related field (experience)
- 8+ years of experience in machine learning operations or DevOps with a focus on ML (experience)
- Proven track record of deploying ML models at scale in production environments (experience)
- Strong understanding of ML pipelines, model monitoring, and lifecycle management (experience)
Preferred Qualifications
- Experience with Autodesk products or AEC industry (experience)
- PhD in a relevant field (experience)
- Contributions to open-source MLOps projects (experience)
- Familiarity with federated learning or edge ML deployment (experience)
Responsibilities
- Design and implement MLOps frameworks for end-to-end ML workflows
- Collaborate with cross-functional teams to integrate ML models into Autodesk applications
- Optimize infrastructure for ML training and inference on cloud and on-premises systems
- Monitor and troubleshoot ML systems for performance and reliability
- Drive best practices in CI/CD for machine learning and mentor junior engineers
Benefits
- general: Competitive salary and performance bonuses
- general: Comprehensive health, dental, and vision insurance
- general: 401(k) matching and retirement plans
- general: Flexible work arrangements and remote options
- general: Professional development opportunities and tuition reimbursement
- general: Employee stock purchase plan and wellness programs
Tags & Categories
Answer 10 quick questions to check your fit for Principal Machine Learning Operations Engineer @ Autodesk.
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Principal Machine Learning Operations Engineer
Autodesk
Principal Machine Learning Operations Engineer
Job Description
Principal Machine Learning Operations Engineer
📋 Job Overview
The Principal Machine Learning Operations Engineer at Autodesk leads the design, development, and deployment of scalable MLOps infrastructure to support machine learning initiatives. This role involves collaborating with data scientists and engineers to operationalize ML models, ensuring reliability, efficiency, and integration with Autodesk's cloud platforms. The position focuses on advancing AI capabilities in design and engineering software products.
📍 Location: Bengaluru
📅 Posted: Posted 30+ Days Ago
🎯 Key Responsibilities
- Design and implement MLOps frameworks for end-to-end ML workflows
- Collaborate with cross-functional teams to integrate ML models into Autodesk applications
- Optimize infrastructure for ML training and inference on cloud and on-premises systems
- Monitor and troubleshoot ML systems for performance and reliability
- Drive best practices in CI/CD for machine learning and mentor junior engineers
✅ Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or related field
- 8+ years of experience in machine learning operations or DevOps with a focus on ML
- Proven track record of deploying ML models at scale in production environments
- Strong understanding of ML pipelines, model monitoring, and lifecycle management
⭐ Preferred Qualifications
- Experience with Autodesk products or AEC industry
- PhD in a relevant field
- Contributions to open-source MLOps projects
- Familiarity with federated learning or edge ML deployment
🛠️ Required Skills
- Proficiency in Python, Java, or Scala for ML engineering
- Expertise in ML frameworks like TensorFlow, PyTorch, or scikit-learn
- Experience with Kubernetes, Docker, and container orchestration
- Knowledge of cloud platforms such as AWS, Azure, or GCP
- Skills in CI/CD tools like Jenkins, GitLab CI, or Kubeflow
- Strong problem-solving and communication skills
- Familiarity with data versioning tools like DVC and monitoring with Prometheus
🎁 Benefits & Perks
- Competitive salary and performance bonuses
- Comprehensive health, dental, and vision insurance
- 401(k) matching and retirement plans
- Flexible work arrangements and remote options
- Professional development opportunities and tuition reimbursement
- Employee stock purchase plan and wellness programs
Locations
- Bengaluru, India
Salary
Estimated Salary Rangemedium confidence
3,500,000 - 5,500,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python, Java, or Scala for ML engineeringintermediate
- Expertise in ML frameworks like TensorFlow, PyTorch, or scikit-learnintermediate
- Experience with Kubernetes, Docker, and container orchestrationintermediate
- Knowledge of cloud platforms such as AWS, Azure, or GCPintermediate
- Skills in CI/CD tools like Jenkins, GitLab CI, or Kubeflowintermediate
- Strong problem-solving and communication skillsintermediate
- Familiarity with data versioning tools like DVC and monitoring with Prometheusintermediate
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or related field (experience)
- 8+ years of experience in machine learning operations or DevOps with a focus on ML (experience)
- Proven track record of deploying ML models at scale in production environments (experience)
- Strong understanding of ML pipelines, model monitoring, and lifecycle management (experience)
Preferred Qualifications
- Experience with Autodesk products or AEC industry (experience)
- PhD in a relevant field (experience)
- Contributions to open-source MLOps projects (experience)
- Familiarity with federated learning or edge ML deployment (experience)
Responsibilities
- Design and implement MLOps frameworks for end-to-end ML workflows
- Collaborate with cross-functional teams to integrate ML models into Autodesk applications
- Optimize infrastructure for ML training and inference on cloud and on-premises systems
- Monitor and troubleshoot ML systems for performance and reliability
- Drive best practices in CI/CD for machine learning and mentor junior engineers
Benefits
- general: Competitive salary and performance bonuses
- general: Comprehensive health, dental, and vision insurance
- general: 401(k) matching and retirement plans
- general: Flexible work arrangements and remote options
- general: Professional development opportunities and tuition reimbursement
- general: Employee stock purchase plan and wellness programs
Tags & Categories
Answer 10 quick questions to check your fit for Principal Machine Learning Operations Engineer @ Autodesk.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs