Hi,
I hope this email finds you well.
My name is Shubham, and I am a Technical Recruiter from Empower Professionals Inc. I came across your profile and wanted to reach out regarding a “MLOPS Engineer - CGEMJP00269602” role with one of our clients at location “Remote”. Please let me know if you are available in the job market and interested in this role (see the job description below) - if so, we can connect and speak further.
Role: MLOPS Engineer - CGEMJP00269602
Duration: 12 Months
Location: Remote
Job Description:
To enhance our Marine-Operations Performance Monitoring & Forecasting capabilities: - MIAP Performance Monitoring: Includes code refactoring and enhancements on a dynamic, two-step regression model used to forecast performance of different shipboard systems (e.g. HVAC, Service Power).
- Fuel Forecasting: Creating an enhanced fuel forecasting model accounting for additional features (e.g. fuel type mix, speed, weather) and serving model through a Container App or Endpoint for Business Planning Teams to simulate fuel costs based on different deployment scenarios.
Note: - Most important skill set is to be an excellent software engineer in Python. Should also know PySpark, Python Package Management, and MLFlow.
- AzureDevOps/MLOps: A MLOps Engineer will enhance the AzureDevOps/MLOps capabilities of MARC. Proper adherence to best practices in MLOps will ensure that MARCs pricing and inventory automation processes are being properly developed, deployed, and monitored in a secure and efficient manner to reduce operational risks and increase system scalability.
- ML Algorithm and techniques
- Feature selection & engineering, identifying, and selecting relevant features and engineering new features to improve model performance.
- Machine Learning frameworks such as TensorFlow, PyTorch etc.
- Creating and maintaining Python libraries for machine learning that provides a range of algorithms for classification, regression, clustering etc
- Skills to write efficient and scalable code for data processing, model training & deployment.
- Selecting appropriate ML algorithms and training them on the preprocessed data to create accurate predictive models.
- Cloud computing platform experience (preferably in Azure)
- Cloud based ML Services (preferred Azure ML)
- Azure services, such as ADF, Azure Functions, Azure Cosmos DB etc.
- Azure DevOps Principles & practices, including CI/CD pipelines.
- Azure Security Management for security policies, access controls
- Azure Active Directory, network security groups
- Strong data analytics skills for data profiling to train the model.
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