GCP Cloud ML/Ops Engineer
Description For GCP Cloud ML/Ops Engineer
Rackspace is seeking a GCP Cloud ML/Ops Engineer to join their team in Bangalore, India. This role requires expertise in public cloud services, particularly GCP, and experience with MLOps tools like VertexAI and Kubeflow Pipelines. The ideal candidate will have strong skills in machine learning frameworks, LLMOps concepts, and DevOps principles. Key responsibilities include building end-to-end data pipelines, deploying ML models in GCP, and working with SQL, Java, and Python for data analysis. The role demands a technical degree in Computer Science or related field, with 4+ years of experience in ML Ops. This position offers a hybrid work environment, requiring 3 days a week in the office. Join Rackspace to contribute to cutting-edge cloud and AI technologies, working with a team that values innovation and adaptability in the rapidly evolving AIOps landscape.
Responsibilities For GCP Cloud ML/Ops Engineer
- Building end-to-end data pipelines
- Deploying ML models in GCP
- Working with SQL, Java, Python for data analysis
- Implementing MLOps practices and tools
- Applying DevOps principles and CI/CD practices
- Managing the entire ML lifecycle
- Setting up monitoring/alerting tools and access controls
- Collaborating with cross-functional teams
Requirements For GCP Cloud ML/Ops Engineer
- Expertise in public cloud services, particularly in GCP
- Experience working with VertexAI / Kubeflow Pipelines or other MLOps tools like MLFlow
- Experience with machine learning frameworks (TensorFlow, PyTorch) and libraries (e.g., scikit-learn, HuggingFace)
- Knowledge of prompt engineering methods, LangChain, Vector databases and machine learning algorithms
- Knowledge of LLMOps concepts and practices
- Experience in Infrastructure and Applied DevOps principles
- Knowledge of containerization technologies such as Docker and Kubernetes
- Strong programming abilities in SQL, Java and Python
- Proven experience with the entire ML lifecycle
- Familiarity with model performance monitoring, data drift detection, and anomaly detection
- Strong understanding of IT infrastructure and operations
- Strong communication skills
- Willingness to adapt to new technologies and methodologies
- Overall 4+ years experience in ML Ops
- 2+ years of experience building end-to-end data pipelines
- 2+ years of experience building and deploying ML models in a GCP
- 3+ years of experience working with SQL, Java, Python for data analysis
- Technical degree: Computer Science, software engineering or related
- Based in Bangalore and willing to work from the office 3 days a week
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