Job Title:  ML OPS Engineer

Location: Orlando, FL (Onsite)

Duration: 06+ Months


*Send me the resumes to venuelika...@thetiltedge.com
<venuelika...@thetiltedge.com>*



*Job Description – *

Overall 10 years out of 5-8 years relevant experience in MLOps.

Azure + Terraform IAC, ML FLow and ML re-training pipelines

can support the team with deploying LLMs, ML inference APIs in Azure oor
Databricks

Can deploy monitoring and full set of observability set.

Deep quantitative/programming background with a degree (Bachelor’s) in a
highly analytical discipline, like Statistics, Economics, Computer Science,
Mathematics, Operations Research, etc



*Responsibilities:*

Design and implement cloud solutions, build MLOps on Azure cloud

Build CI/CD pipelines orchestration by Azure Devops or similar tools

Data science model review, code refactoring and optimization,
containerization, deployment, versioning, and monitoring of its quality

Data science models testing, validation and tests automation

Communicate with a team of data scientists, data engineers and architect,
document the processes.



*Requirements:*

Overall 10 years out of 5-8 years of experience in managing machine
learning projects end-to-end, with the last 18 months focused on MLOps.

Monitoring Build & Production systems using automated monitoring and alarm
tools

Knowledge of machine learning frameworks: TensorFlow, PyTorch, Keras,
Scikit-Learn

Knowledge on building pipelines using synapse, databricks end to end.

Experience in API integration and data feeds with social
analytics(Facebook, Instagram, Twitter).

Experience with MLOps tools such as ModelDB, Kubeflow, Pachyderm, and Data
Version Control (DVC)

Experience in supporting model builds and model deployment for IDE-based
models and autoML tools, experiment tracking, model management, version
tracking & model training (Dataiku, Datarobot, Kubeflow, MLflow, neptune.ai)
will be an addon, model hyperparameter optimization, model evaluation, and
explainability (SHAP, Tensorboard)

Experience in Databricks, Azure DataLake Gen2 and Unity Catalog

Ability to understand tools used by data scientist and experience with
software development and test automation

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