On-site
Mid Level
Full Time
Posted January 12, 2026
Tech Stack
ml-flow
mlflow
kubeflow
vertex
google-cloud-platform
amazon-web-services
microsoft-azure
h2o
java
python
elearning-lms
scikit-learn
xgboost
tensorflow
pytorch
docker
kubernetes
airflow
apache-airflow
spark
appcast
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Rivago infotech inc, is seeking the following. Apply via Dice today!
**Role : MLOPS Engineer**
**Location : Concord, CA (100% Onsite)**
**Key Responsibilities**
- 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., Google Cloud Platform, 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
**Qualifications**
- 10+ Years of professional experience in Software Engineering & 3+ Years in AIML, 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.