GCP MLOps

Job Description: GCP MLOps Engineer (8-10 Years Experience)

Location: Hyderabad / Bangalore

Role Overview

We are seeking a highly skilled and experienced GCP MLOps Engineer with 8-10 years of experience 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. The role demands expertise in Google Cloud Platform (GCP), Concord, PLX, SQL, Salesforce, and machine learning frameworks.

Key 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.

1. Cloud Infrastructure:

• 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.

1. 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.

1. 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.

1. Collaboration:

• 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.

1. Performance Tuning:

• Monitor and enhance the performance of ML models in production.
• Debug and resolve issues related to data pipelines, models, and cloud environments.

1. Compliance and Security:

• Ensure all solutions comply with security, privacy, and compliance standards.
• Manage sensitive data securely in accordance with organizational policies.

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.

1. Machine Learning:

• 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.

1. DevOps and CI/CD:

• Experience with CI/CD tools like Jenkins, GitLab, or CircleCI for ML pipelines.

1. 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.

1. Preferred:

• 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.