Job Title: Senior MLops Engineer
Location: Remote
Employment Type: contract must have to work US timings - US client
Job Summary:
These engineers will perform hands-on work across data operations, model monitoring, automation, drift detection, and ML pipeline development.
They act as core technical contributors, supporting planning, discovery, and implementation of machine-learning solutions in production environments.
What These Engineers Will Do- Build data pipeline monitoring and observability capabilities
- Develop anomaly detection workflows with automated alerting
- Design and maintain ground-truth labeling and validation frameworks
- Scale monitoring pipelines across all production ML models using consistent standards
- Automate drift detection, label validation, and data quality guardrails
- Support onboarding of new models, simulations, pipelines, and automation workflows
- Create and enhance mock or synthetic test data frameworks for model feature testing
- Integrate solutions into existing enterprise ML platforms and ensure production readiness
Target Background- 610 years of experience in MLOps, ML Engineering, or Data Engineering
- Strong exposure to ML automation and production ML systems
- Hands-on experience with:
- Model monitoring and observability
- Ground-truth and validation frameworks
- Drift detection and data-quality checks
- End-to-end ML pipeline automation
Key Skills to Screen For- Deep MLOps engineering expertise
- Strong pipeline reliability and production hardening skills
- Experience designing monitoring frameworks for ML systems
- Proven ability to support and scale ML models in production
- Hands-on proficiency with Python and Spark
- Experience with workflow orchestration, CI/CD, and observability tools
- Ability to work effectively across Data, ML, and Platform teams
