ML Ops

ML Ops

Key Responsibilities 
A total of 5+ yrs of exp in ML Ops Platform support role 
Develop and maintain CI/CD pipelines for ML models. 
Automate model deployment, monitoring, and performance tracking. 
Collaborate with data scientists to ensure models are production-ready. 
Implement tools for model versioning, testing, and validation. 
Ensure compliance with data governance and security standards. 
Optimize ML workflows for scalability and cost-efficiency. 
Troubleshoot and resolve issues related to model performance and infrastructure. 
Stay updated with the latest MLOps tools and best practices. 

Support continuous improvement by identifying and solving opportunities. 
Bachelor or Master degree in Computer Science, Data Science, or related field. 
3+ years of experience in MLOps, DevOps, or related roles. 
Strong programming skills in Python; familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn. 
Knowledge on Sagemaker, Shakudo 
Experience with cloud platforms (AWS, Azure, GCP). 
Proficiency in containerization (Docker) and orchestration (Kubernetes). 
Knowledge of CI/CD tools (e.g., Jenkins, GitHub Actions). 
Familiarity with monitoring tools (Prometheus, Grafana). 
Excellent problem-solving and communication skills.

Mandatory Skills

Python
SQL
Machine Learning