
Gcp Ai Solution Architect with Mlops/genai
2 days ago
Job Role: GCP AI Solution architect with MLOps/GenAI
Location
- Pune/Bangalore/Hyderabad/Mumbai/Chennai/Noida
Budget: Open
Job Overview:
We are seeking a talented and experienced GCP Solution Architect with a strong background in MLOps to join our team.
You will collaborate with cross-functional teams to ensure the successful deployment and scaling of machine learning models.
Key Responsibilities:
- Develop and manage end-to-end MLOps pipelines, including data preprocessing, model training, validation, and deployment.
- Collaborate with data scientists, engineers, and stakeholders to understand business requirements and translate them into technical solutions.
- Optimize cloud resources for performance, cost efficiency, and security.
- Provide guidance on best practices for GCP services related to machine learning, such as AI Platform, BigQuery, Cloud Functions, and Kubernetes Engine.
- Monitor and troubleshoot ML models in production, ensuring high availability and performance.
- Stay current with industry trends and emerging technologies in GCP and MLOps.
Qualifications: GCP Cloudstack - end to end
- Bachelor’s degree in Computer Science, Information Technology, or a related field (Master’s preferred).
- Proven experience as a Solution Architect with a focus on GCP and MLOps.
- Strong understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
- Proficiency in GCP services, particularly those relevant to machine learning and data engineering.
- Experience with containerization technologies (Docker, Kubernetes).
- Familiarity with CI/CD practices and tools related to ML workflows.
- Excellent problem-solving skills and ability to work collaboratively in a team environment.
- Strong communication skills to articulate technical concepts to non-technical stakeholders.
**Job Type**: Contractual / Temporary
Contract length: 6 months
Pay: ₹100,000.00 - ₹130,000.00 per month
Schedule:
- Morning shift
**Experience**:
- total work: 6 years (required)
Work Location: In person
Application Deadline: 21/11/2024
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