Job Title: AI ML OPS lead Location: Remote (EST time zone only ) Term: Contract Job Summary: We’re looking for a skilled AI/ML Ops Engineer to bridge the gap between machine learning development and scalable, reliable production systems. You’ll be responsible for building and maintaining the infrastructure that enables rapid experimentation, deployment, and monitoring of ML models in real-world environments. Key Responsibilities: Design and implement CI/CD pipelines for ML models. Automate model training, testing, deployment, and monitoring workflows. Collaborate with data scientists to productionize ML models. Manage model versioning, reproducibility, and rollback strategies. Ensure scalability, security, and compliance of ML systems. Monitor model performance and data drift in production. Optimize infrastructure for cost and performance. Required Qualifications: 8-10+ years of experience in DevOps, ML Ops, or ML Engineering. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with containerization (Docker) and orchestration (Kubernetes). Familiarity with cloud platforms (AWS, Azure, or GCP). Strong understanding of CI/CD tools (e.g., GitHub Actions, Jenkins). Knowledge of monitoring tools (e.g., Prometheus, Grafana). Preferred Qualifications: Experience with feature stores and model registries (e.g., ML flow, Feast). Understanding of data governance and responsible AI practices. Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.