ML Ops Engineer
OMG Tech Partners
contract
Posted on:
Location Type: Office
Location: Concord • California • United States
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Salary
💰 $55 - $60 per hour
Tech Stack
About the role
- Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.
- Automate model training, testing, deployment, and monitoring in cloud environments (e.g., GCP, AWS, Azure).
- Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.
- Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability).
- Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs.
- Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment.
Requirements
- 10+ Years of professional experience in Software Engineering.
- 3+ Years in AIML, and Machine Learning Model Operations.
- Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
- Experience with cloud platforms and containerization (Docker, Kubernetes).
- Hands-on experience delivering 3-4 end-to-end Production projects.
- Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.
- Solid understanding of software engineering principles and DevOps practices.
- Good communication skills and able to manage stakeholders.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine LearningML pipelinesJavaPythonSQLscikit-learnXGBoostTensorFlowPyTorchDevOps
Soft Skills
communicationstakeholder management