MLOps Engineer

The MLOps Engineer (GCP Specialization) is responsible for designing, implementing, and maintaining infrastructure and processes on Google Cloud Platform (GCP) to enable the seamless development, deployment, and monitoring of machine learning models s role bridges data science and data engineering, Infrastructure, ensuring that machine learning systems are reliable, scalable, and optimized for GCP environments.

• Model Deployment:
  Design and implement pipelines for deploying machine learning models into production using GCP services suchas AI Platform, Vertex AI, or Cloud Run, Cloud Composer ensuring high availability and performance.
• Infrastructure Management:
  Build and maintain scalableGCP-based infrastructure using services like Google Compute Engine, Google Kubernetes Engine (GKE), and Cloud Storage to support model training,deployment, and inference.
• Automation:
  Develop automated workflows for data ingestion, model training, validation, and deployment using GCP tools like Cloud Composer, and CI/CD pipelines integrated with Git Lab and Bitbucket Repositories.
• Monitoring and Maintenance:
  Implement monitoring solutions using Google Cloud Monitoring and Logging to track model performance, data drift, and system health, and take corrective actions asneeded.
• Collaboration:
  
  Work closely with data scientists, Data engineers, Infrastructure and Dev Ops teams to streamline the ML lifecycleand ensure alignment with business objectives.
• Versioning and Reproducibility:
  Manage versioning of datasets, models, and code using GCP tools like Artifact Registry or Cloud Storage to ensure reproducibility and traceability of machine learning experiments.
• Optimization:
  Optimize model performance and resource utilization on GCP, leveraging containerization with Docker and GKE, and utilizing cost-efficient resources like preemptible VMs or Cloud TPU/GPU.
• Security and Compliance:
  Ensure ML systems comply withdata privacy regulations (e.g., GDPR, CCPA) using GCP’s security toolslike Cloud IAM, VPC Service Controls, and Data Loss Prevention (DLP).
• Tooling:
  Integrate GCP-native tools (e.g., Vertex AI,Cloud composer) and open-source MLOps frameworks (e.g., MLflow, Kubeflow) to support the ML lifecycle.

• Proficiency in programming languages such as Python.
• Expertise in GCP services, including Vertex AI, Google Kubernetes Engine (GKE), Cloud Run, Big Query, Cloud Storage, and Cloud Composer, Data proc or PySpark and managed Airflow.
• Experience with infrastructure-as-code - Terraform.
• Familiarity with containerization (Docker, GKE) andCI/CD pipelines, Git Lab and Bitbucket.
• Knowledge of ML frameworks (Tensor Flow, PyTorch,scikit-learn) and MLOps tools compatible with GCP (MLflow, Kubeflow) andGen AI RAG applications.
• Understanding of data engineering concepts, includingETL pipelines with Big Query and Dataflow, Dataproc - Pyspark.

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, cross-functional environment.

• Experience with large-scale distributed ML systems onGCP, such as Vertex AI Pipelines or Kubeflow on GKE, Feature Store.
• Exposure to Generative AI (GenAI) and Retrieval-Augmented Generation (RAG) applications and deployment strategies.
• Familiarity with GCP’s model monitoring tools and techniques for detecting data drift or model degradation.
• Knowledge of microservices architecture and API development using Cloud Endpoints or Cloud Functions.
• Google Cloud Professional certifications (e.g.,Professional Machine Learning Engineer, Professional Cloud Architect)

Kanini Software Solutions, Inc. does not discriminate in employment matters on the basis of race, gender, religion, age, national origin, citizenship, veteran status, family status, disability status, or any other protected class. We support workplace diversity. If you have a disability, please let us know if there is anything we can do to improve the interview process for you; we’re happy to accommodate.

Kanini Software Solutions, Inc., 25 Century Blvd., Ste. 602, Nashville, TN 37214.