Senior Cloud Machine Learning Engineer
7 days ago
About the Role:
This is a senior-level position that requires a highly skilled and experienced GCP MLOps Engineer to join our team in Hyderabad or Bangalore. The ideal candidate will have a strong background in cloud-based machine learning operations, data engineering, and end-to-end ML pipeline automation.
Main Responsibilities:
1. MLOps Implementation:
• Design, develop, and deploy scalable MLOps pipelines on Google Cloud Platform (GCP).
• Automate end-to-end machine learning workflows, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
2. Cloud Infrastructure Management:
• Architect and manage GCP services such as BigQuery, Vertex AI, Dataflow, AI Platform, Cloud Storage, and others for ML projects.
• Optimize cloud infrastructure to ensure cost-effectiveness and performance.
3. Data Integration and Management:
• Work with SQL to query and manage large-scale data from diverse sources.
• Integrate Salesforce data and other enterprise platforms into ML pipelines.
• Ensure seamless data flow between various systems using PLX and Concord.
4. Model Deployment and Monitoring:
• Deploy machine learning models in production environments with proper monitoring and logging.
• Implement CI/CD pipelines for model versioning and updates.
5. Collaboration and Technical Leadership:
• Collaborate with data scientists, data engineers, and stakeholders to ensure seamless integration of ML models into business workflows.
• Provide technical leadership and mentorship to junior team members.
Required Skills and Qualifications:
1. Technical Expertise:
• 5+ years of hands-on experience with Google Cloud Platform (GCP).
• Strong expertise in MLOps tools and frameworks (e.g., Vertex AI, Kubeflow, TensorFlow Extended).
• Proficiency in Concord and PLX for data pipeline and workflow orchestration.
• Solid understanding of SQL and experience in writing optimized queries for large datasets.
• Experience in integrating and managing Salesforce data.
2. Machine Learning Knowledge:
• Deep understanding of ML lifecycle management, model deployment, and monitoring.
• Strong knowledge of Python/R and ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
3. DevOps and CI/CD Knowledge:
• Experience with CI/CD tools like Jenkins, GitLab, or CircleCI for ML pipelines.
4. Soft Skills:
• Strong problem-solving skills and ability to work in a fast-paced environment.
• Excellent communication and collaboration skills to work with cross-functional teams.
• Ability to mentor and guide junior engineers.
Preferred Qualifications:
• Experience with Salesforce Einstein Analytics.
• Exposure to cloud cost optimization strategies.
Education:
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
Salary: ₹2000000 - ₹3500000 per annum
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