Posted:4 days ago|
Platform:
Hybrid
Full Time
- Experience: 7+ years in data engineering, 3+ years as an MLOps engineer.
- MLOps Pipelines: Design, develop, and implement using tools like MLflow and Apache Airflow.
- Cloud Experience: Working experience with AWS and Databricks.
- Technical Proficiency: Strong in Python, PySpark, SQL, machine learning, NLP, deep learning, and AWS services (SageMaker, BedRock, EC2, Lambda, S3, Glue Tables).
- Configuration Management: Experience with Ansible, Terraform, and building CI/CD pipelines.
Responsibilities
- Automate ML Lifecycle: From data ingestion to deployment and monitoring.
- Collaborate with Data Scientists: Understand data science lifecycle, translate needs into production-ready solutions.
- Model Deployment and Monitoring: Strong in ML model deployment, AI ML pipeline, and model monitoring.
- Communication: Excellent written and verbal communication skills.
Desired Qualities
- Analytical Mindset: Ability to interpret data and metrics.
- Collaboration: Technical proficiency and ability to work with technical teams.
- ML Techniques: Familiarity with algorithms like RNN, CNN, GNN, GAN.
Caltek Solutions
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