ThreatXIntel
Website:
threatxintel.com
Company:
https://www.linkedin.com/company/threatxintel
Seniority: Mid-Senior level
Industries: Computer and Network Security
Job details:
Company Description
ThreatXIntel is a growing Cybersecurity, IT Staffing, and Consulting company delivering end-to-end technology and security solutions.
We are hiring for our corporate client. ThreatXIntel is the official hiring partner for this requirement
About the role
We are looking for a Senior MLOps / ML Engineer with strong hands-on experience in Snowflake, Azure Machine Learning, Python, MLOps, ML AIOps, and production ML model deployment.
The environment is heavily centered around Snowflake, and we are particularly interested in candidates who can demonstrate real-world production ML deployments.
Candidates should be able to clearly explain the models they have deployed, the deployment architecture, monitoring approach, CI/CD pipelines, model/data drift handling, and automated retraining process.
🔹 Key Responsibilities
- Design, implement, and manage end-to-end ML lifecycle automation, including model training, validation, deployment, monitoring, and retraining.
- Build and maintain CI/CD pipelines for integration, testing, and production deployment of ML models.
- Deploy, monitor, and manage ML models in production with focus on availability, scalability, reliability, and inference performance.
- Implement model monitoring, logging, and alerting to track model performance and detect model/data drift.
- Design automated mechanisms to trigger model retraining based on performance degradation or drift.
- Work closely with Data Engineers, Data Scientists, and Platform teams to ensure reliable Snowflake-based data pipelines and ML workflows.
- Manage ML artifact versioning, governance, traceability, security, compliance, and audit requirements.
- Support AI/ML testing and production reliability initiatives.
- Optimize ML workflows and infrastructure for scalable enterprise production environments.
🔹 Mandatory Skills
- Snowflake – Strong hands-on experience
- MLOps
- Azure Machine Learning
- Python
- Machine Learning / Industrial AI
- ML AIOps
- Production ML Model Deployment
- ML Lifecycle Management
- Thought Machine
🔹 Good to Have
- AI/ML Testing
- CI/CD Architecture
- Azure DevOps
- Model Monitoring & Observability
- Data/Model Drift Detection
- Automated Model Retraining
- ML Governance
- Model Versioning & Traceability
- Cloud-based ML Infrastructure
Engagement: Part-Time | Freelance
Work Mode: Remote
Level: Senior
Click on Apply to know more.
