
AI Monitoring Professional
2 weeks ago
Location - Remote
Shit Timings - Night shifts
Demand Name : AI Monitoring Professional
Engagement & Project Overview
An AI model trainer brings specialised knowledge in developing and fine-tuning machine learning models. They can ensure that your models are accurate, efficient, and tailored to your specific needs. Hiring an AI model trainer and tester can significantly enhance our data management and analytics capabilities
Job Description
1. Expertise in Model Development:
Develop and fine-tune machine learning models.
Ensure models are accurate, efficient, and tailored to our specific needs.
2. Quality Assurance:
Rigorously evaluate models to identify and rectify errors.
Maintain the integrity of our data-driven decisions through high performance and reliability.
3. Efficiency and Scalability:
Streamline processes to reduce time-to-market.
Scale AI initiatives and ML engineering skills effectively with dedicated model training and testing.
4. Production ML Monitoring & MLOps:
Implement and maintain model monitoring pipelines to detect data drift, concept drift, and model performance degradation.
Set up alerting and logging systems using tools such as Evidently AI, WhyLabs/Prometheus + Grafana or cloud-native solutions (AWS SageMaker Monitor, GCP Vertex AI, Azure Monitor).
Collaborate with teams to integrate monitoring into CI/CD pipelines, using platforms like Kubeflow, MLflow, Airflow, and
Define and manage automated retraining triggers and model versioning strategies.
Ensure observability and traceability across the ML lifecycle in production environments.
Preferred Experience /Qualification /Certifications
Qualifications:
5+ years of experience in the respective field.
Proven experience in developing and fine-tuning machine learning models.
Strong background in quality assurance and model testing.
Ability to streamline processes and scale AI initiatives.
Innovative mindset with a keen understanding of industry trends.
License/Certification/Registration
Expected No. of Interviews
1-2
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