Machine Learning Engineer (ANPR System)
Salt are recruiting for an immediate requirement with a local government client of ours who is looking for a Machine Learning Ops Engineer (Data & Analytics).
This will be an Inside IR35 contract for 12 months initially. It would be a mainly hybrid role with 2 days a week expected in office, based in South East London.
Your main focus of the project will be around the ANPR (Automatic Number Plate Recognition) system. You will be responsible in delivering enhancements and optimizations to our client's secondary ANPR system so that it is fully refined.
Key experiences:
- Experience working on ANPR systems is required.
- Strong expertise in Python and Scala, with proficiency in machine learning libraries (eg, PyTorch, ONNX, XGBoost).
- Proven experience deploying ML models in production and optimizing their performance.
- Knowledge of MLOps best practices, including model development, deployment, and monitoring.
- Expertise in building MLOps pipelines on Azure Cloud (Azure DevOps, Functions, ML, Databricks, CosmosDB).
- Familiarity with CI/CD principles, version control (Git, MLFlow), and automated testing.
Reference: 2840116693
Machine Learning Engineer (ANPR System)
Posted on Oct 23, 2024 by Salt
Salt are recruiting for an immediate requirement with a local government client of ours who is looking for a Machine Learning Ops Engineer (Data & Analytics).
This will be an Inside IR35 contract for 12 months initially. It would be a mainly hybrid role with 2 days a week expected in office, based in South East London.
Your main focus of the project will be around the ANPR (Automatic Number Plate Recognition) system. You will be responsible in delivering enhancements and optimizations to our client's secondary ANPR system so that it is fully refined.
Key experiences:
- Experience working on ANPR systems is required.
- Strong expertise in Python and Scala, with proficiency in machine learning libraries (eg, PyTorch, ONNX, XGBoost).
- Proven experience deploying ML models in production and optimizing their performance.
- Knowledge of MLOps best practices, including model development, deployment, and monitoring.
- Expertise in building MLOps pipelines on Azure Cloud (Azure DevOps, Functions, ML, Databricks, CosmosDB).
- Familiarity with CI/CD principles, version control (Git, MLFlow), and automated testing.
Reference: 2840116693
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