Mlops| Azure|Data Bricks
Primary Skills: MLops, Azure Data Bricks
Total experience- 5 to 8 years
Location: Pune/ Mumbai/ Hyderabad/ Chennai/ Bangalore/ Kolkata
Notice period- Immediate to 30 days
Mandatory Skills - ML Ops – Azure
Job Title
MLOps Engineer
Requirements
• Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
• Strong software engineering skills in complex, multi-language systems
• Fluency in Python
• Comfort with Linux administration
• Experience working with cloud computing and database systems
• Experience building custom integrations between cloud-based systems using APIs
• Experience developing and maintaining ML systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
• Ability to translate business needs to technical requirements
• Strong understanding of software testing, benchmarking, and continuous integration
• Exposure to machine learning methodology and best practices
• Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)
• Experience with OpenAI / ChatGPT and cognitive services
Competencies
• Strong problem solving skills.
• Excellent written and verbal communication skills for coordinating across teams.
• Drive to learn and master new technologies and techniques
Apply Now
Total experience- 5 to 8 years
Location: Pune/ Mumbai/ Hyderabad/ Chennai/ Bangalore/ Kolkata
Notice period- Immediate to 30 days
Mandatory Skills - ML Ops – Azure
Job Title
MLOps Engineer
Requirements
• Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
• Strong software engineering skills in complex, multi-language systems
• Fluency in Python
• Comfort with Linux administration
• Experience working with cloud computing and database systems
• Experience building custom integrations between cloud-based systems using APIs
• Experience developing and maintaining ML systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
• Ability to translate business needs to technical requirements
• Strong understanding of software testing, benchmarking, and continuous integration
• Exposure to machine learning methodology and best practices
• Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)
• Experience with OpenAI / ChatGPT and cognitive services
Competencies
• Strong problem solving skills.
• Excellent written and verbal communication skills for coordinating across teams.
• Drive to learn and master new technologies and techniques