Machine Learning Engineers create new systems and machines that are powered with artificial intelligence to complete assigned tasks without prompting. Companies with ML Engineers are seeing incredible investments rolling in for their projects, as deep learning machines and technologies are being sought and utilized in virtually every sector. Deep learning and AI are considered by experts as the wave of the tech future, with Machine Learning Engineers taking the helm and creating incredible intelligent products. Responsibilities
- Engaging in data modeling and evaluation
- Developing new software and systems
- Designing trials and tests to measure the success of software and systems
- Working with teams and alone to design and implement AI models
These Would Also Be Nice
- An aptitude for statistics and calculating probability
- Familiarity in Machine Learning frameworks, such as Scikit-learn, Pytorch and Keras TensorFlow
- An eagerness to learn
- Determination - even when experiments fail, the ability to try again is key
- A desire to design AI technology that better serves humanity
- Experience building large-scale machine learning pipelines, using Kubeflow, Google Cloud ML, AWS Sagemaker, Microsoft Azure ML, Spark MLflow, or others.
- Experience implementing machine learning models using Scikit-learn, TensorFlow, Keras, Spark MLlib, PyTorch, MXNet, CNTK, or other libraries.
- Proficiency in one or more or programming languages: Python, Java, Scala, Go, C++, etc...
- Fluency in SQL optimization, Jupyter Notebooks.
- Good communication - even with those who do not understand AI
- Creative and critical thinking skills
- A willingness to continuously take on new projects
- Understanding the needs of the company
- Being results-driven