ML Architect
Oracle
We are seeking a Machine Learning & Deep Learning Lead/Architect to design and operationalize scalable ML/DL solutions using open-source AI frameworks and Oracle Cloud Infrastructure (OCI). In this role, you will define end-to-end architecture for model development and production deployment, building robust MLOps pipelines for training, automated release, monitoring, governance, and continuous improvement. You will leverage OCI Data Science, OCI AI Services, OCI Object Storage, and GPU instances to deliver cost-effective, secure, and high-performing ML workloads, while integrating tools such as MLflow, Kubeflow, and Airflow for reproducibility, versioning, and CI/CD. You will partner closely with product, data, and engineering teams to align technical choices with business outcomes, establish best practices for reliability and compliance, and mentor practitioners across modern ML/DL frameworks and cloud-native delivery. This role requires strong technical depth, architectural leadership, and excellent stakeholder communication.
Skills Required
- 10+ years of ML/DL experience, with 3+ years in architecture/leadership roles.
- Proven track record of deploying ML/DL solutions using open-source frameworks and MLOps practices.
- Hands-on experience with Oracle Cloud Infrastructure (OCI Data Science, AI Services, Object Storage, GPU/accelerators).
- Strong knowledge of MLOps tools
- Excellent leadership, communication, and stakeholder management skills.
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We are seeking a Machine Learning & Deep Learning Lead/Architect with expertise in open-source AI frameworks, Oracle Cloud Infrastructure (OCI), and MLOps practices. The role involves architecting scalable ML/DL solutions, ensuring robust lifecycle management, and operationalizing models in production using OCI-native services and open-source MLOps tools.
Career Level - IC3
Key Responsibilities
- Architect ML/DL solutions using open-source frameworks (TensorFlow, Hugging Face, Scikit-learn).
- Design and implement MLOps pipelines for model training, deployment, monitoring, and governance.
- Leverage OCI services (OCI Data Science, OCI AI Services, OCI Object Storage, OCI GPU instances) for scalable ML workloads.
- Integrate open-source MLOps tools (MLflow, Kubeflow, Airflow) with OCI-native services.
- Define standards for reproducibility, versioning, and automated CI/CD of ML models.
- Collaborate with product, data, and engineering teams to align ML/DL architecture with business goals.
- Ensure cost optimization, scalability, and compliance in ML/DL deployments on OCI.
- Mentor teams in open-source ML/DL frameworks, OCI cloud-native practices, and MLOps methodologies.
- Stay updated with advancements in open-source AI, OCI services, and MLOps tooling.
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Lead execution of projects across Machine Learning and Deep Learning frameworks
| Category | Skills |
| Programming Languages | Python, Object Oriented Python, C++, Anaconda/Miniconda, OCI Data Science |
| Open Source ML/DL | TensorFlow, Hugging Face Transformers, Scikit-learn |
| Data Handling | Pandas, NumPy, Seaborn, Matplotlib, Open-source ETL tools - PySpark |
| Model Development | Classical ML, CNNs, RNNs, GANs, Transformers, Reinforcement Learning |
| MLOps Practices | Model lifecycle management, CI/CD for ML, Automated retraining, Monitoring & Logging |
| MLOps Tools | MLflow, Kubeflow, Airflow, Docker, Kubernetes, GitOps |
| Oracle Cloud Services | OCI Data Science, OCI AI Services, OCI Object Storage, OCI GPU/Accelerators |
| Architecture Skills | Distributed Systems, Microservices (Flask), API Design (FastAPI) , Cloud-native patterns |
| Mathematics & Stats | Linear Algebra, Probability, Optimization, Statistical Modeling |
| Soft Skills | Leadership, Strategic Thinking, Collaboration, Communication |