Machine Learning Engineer

Responsibility

The common responsibilities for this position include developing and deploying machine learning models to address business needs, designing and implementing reliable and scalable AI pipelines and systems, and optimizing machine learning models for various applications. The role involves collaborating with cross-functional teams, including data scientists and engineers, to integrate ML solutions into existing systems and ensuring the robustness and performance of AI products. Additional responsibilities include conducting data preprocessing, feature engineering, and model optimization, as well as monitoring and enhancing model performance. The engineer will also be tasked with creating production-grade machine learning solutions, developing automated pipelines for model training and monitoring, and staying updated on emerging machine learning technologies and best practices. Furthermore, responsibilities extend to documenting processes, conducting experiments for model evaluation, and supporting the deployment of ML solutions on cloud platforms.

Job Growth

Skills Requirement

The percentages next to each skill reflect the sector’s demands in these respective skills. E.g., 30% means this skill has been listed in 30% of all the job postings in this sector.

• Skill Categories
• Specific Skill Sets

Skills Distribution

The skills distribution tells you what specific skill sets are in demand. E.g., Skills with a distribution of “More than 50%” means that these skills are wanted in more than 50% of the job postings.

• More Than 70%
• More Than 50%
• More Than 30%
• More Than 10%