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MLOps Engineer

  • Location:

    Manchester

  • Contact:

    Gemma Cartney

  • Job ref:

    5939

  • Published:

    about 1 month ago

  • Expiry date:

    2022-06-30

Are you an MLOps Engineer looking for a challenging opportunity to really make a difference in Machine Learning and AI?

Are you a DevOps Engineer with experience working within Machine Learning and AI that would like the opportunity to be part of building next generation AI technology?

Do you want the opportunity to be a big part of helping to excel Machine Learning and Artificial Intelligence technology into the real world?

If so this MLOps opportunity could be the exciting next step in your career.

The responsibilities of the MLOps Engineer are as follows;

• Ensure that the researchers can easily train and deploy machine learning models using industry-standard tools while using the machine learning platforms (e.g. GitHub, Docker, Bash)

• Develop and manage automated machine learning project training pipelines and infrastructure, with an emphasis on scalability, usability, reproducibility, and performance.

• Ensure that best practises for developing, testing, and releasing software are followed.

• Enhance the present model's tracking, versioning, monitoring, and management functions.

To Fulfil these responsibilities of MLOps Engineer you will need the following skills/experience;

• A bachelor's or master's degree in computer science, computer architecture, or a related technical subject, or comparable experience is required.

• 3+ years of software development experience.

• Strong programming skills in Bash and Python.

• Effective communication and documentation techniques.

• Comprehensive knowledge of software testing and DevOps principles

• Extensive knowledge of how to set up, maintain, and automate continuous integration systems.

• A working knowledge of fundamental machine learning concepts such as model parameters, metrics, biases, and datasets.

Optional requirements for the position of MLOps Engineer are;

• Knowledge of containerization tools like Docker.

• Understanding of cloud deployment services (e.g. AWS).

• Production experience with machine learning models.

• Knowledge of MLOps tools (e.g., MLFlow, Kubeflow, and Apache Airflow).

• Working knowledge of distributed systems.

If you are analytically strong and self-directed MLOps Engineer / DevOps who is focused on the development and maintenance of Machine Learning Platforms and would like to join an organisation that is truly pushing the technological boundaries of asset management, retail analytics, supply chain and manufacturing this could be the position for you. To apply for the position of MLOps Engineer please apply today.