Position Details
About this role
This role involves deploying, monitoring, and scaling machine learning models in production environments, collaborating with data scientists and engineers to build scalable AI solutions.
Key Responsibilities
- Deploying ML models
- Collaborating with data scientists
- Supporting ML lifecycle
- Applying best practices in data engineering
- Using modern MLOps tools
Technical Overview
The technical environment includes Python, ML frameworks like TensorFlow and PyTorch, deployment tools such as ONNX and TensorRT, MLflow, Kubeflow, Azure ML Pipelines, and distributed data processing with PySpark.
Ideal Candidate
The ideal candidate is a mid-level AI/ML engineer with strong Python skills and experience with ML frameworks like TensorFlow and PyTorch. They should have familiarity with ML deployment tools, cloud platforms, and distributed data processing, with a collaborative mindset and a passion for continuous learning.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Clearance & Visa
Keywords for Your Resume
Deal Breakers
Lack of experience with ML frameworks (TensorFlow, PyTorch), No experience with ML deployment tools (ONNX, TensorRT), Unwillingness to work in a hybrid environment, No familiarity with distributed data processing (PySpark)
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