MLOP's Engineer
MLOP's Engineer
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Job Description
Responsibilities
- Design, implement, and manage end-to-end ML pipelines for model training, testing, and deployment
- Deploy and maintain machine learning models in production environments
- Develop and optimize data pipelines using SQL (mandatory)
- Work closely with Data Scientists and Data Engineers to operationalize ML models
- Build and maintain CI/CD pipelines for ML workflows
- Monitor model performance and ensure scalability and reliability
- Utilize Databricks for data engineering, model development, and deployment
- Ensure best practices in data governance, versioning, and reproducibility
- Troubleshoot and resolve production issues efficiently
- Strong experience in ML Ops (Model Deployment, Monitoring, CI/CD)
- Hands-on experience with Databricks
- Strong SQL expertise (mandatory) for data manipulation and pipeline development
- Good communication and stakeholder management skills
- Experience with cloud platforms (AWS/Azure/GCP)
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 4+ years of relevant experience in ML Ops / Data Engineering / ML Engineering
More Info
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Key Skills
About Company
Skills:
Azure ML, Docker, Python, Kubernetes, experiment tracking, model versioning, Weights and Biases, MLflow, model serving infrastructure, model monitoring systems, data and feature pipelines, GCP Vertex AI, AWS SageMaker
Skills:
triton , Prometheus, Grafana, Openshift, Splunk, Azure, Kubernetes, AWS, TensorRT-LLM, GitOps, NIM microservices, NVIDIA GPU operator, vLLM, infrastructure-as-code, Azure GPU build environments, container registry, observability
Skills:
Aws Lambda, Python Automation, Cloudformation, Jenkins, Git, MLops, Docker, Terraform, Databricks, Training Pipelines, Feature Store, MLflow, Kubernetes EKS, Model Retraining, SageMaker, Drift Detection, Model Monitoring, Model Deployment, Kubeflow, Inference Pipelines, CI CD for ML
Skills:
Github, MLops, AWS CloudFormation, Apache Airflow, Data Migration, Pyspark, AWS Glue, AWS CDK, AWS Lake Formation, GitHub Actions, AWS SageMaker
Skills:
Elk, Prometheus, Grafana, Docker, Python, AWS, Gcp, Azure, Kubernetes, Arize AI, vector databases, LangSmith, LangGraph, OpenTelemetry, RAG pipelines, Weights Biases, LangChain, AgentOps tools, cloud platforms, PromptLayer, LLM orchestration frameworks, monitoring observability tools, LlamaIndex, context orchestration