London, UK – 3+ Years | Full-Time
We are looking for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.
To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.
Machine Learning Engineer Responsibilities
- Consulting with managers to determine and refine machine learning objectives.
- Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
- Transforming data science prototypes and applying appropriate ML algorithms and tools.
- Ensuring that algorithms generate accurate user recommendations.
- Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
- Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
- Developing ML algorithms to analyze huge volumes of historical data to make predictions.
- Running tests, performing statistical analysis, and interpreting test results.
- Documenting machine learning processes.
- Keeping abreast of developments in machine learning.
Machine Learning Engineer Requirements
- Bachelor's degree in computer science, data science, mathematics, or a related field.
- Master’s degree in computational linguistics, data analytics, or similar will be advantageous.
- At least two years' experience as a machine learning engineer.
- Advanced proficiency with Python, Java, and R code writing.
- Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
- In-depth knowledge of mathematics, statistics, and algorithms.
- Superb analytical and problem-solving abilities.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
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