Software Engineer, Applied ML

About this kind of role

What a Software Engineer, Applied ML usually does. The employer's own details are in the listing.

Typically does: Designs, develops, tests, and maintains machine learning models and algorithms for practical applications. This often involves working with large datasets, evaluating model performance, and integrating models into existing software systems. Responsibilities can include feature engineering, model selection, and optimization to improve accuracy and efficiency. Engineers in this role frequently collaborate with data scientists and other engineers to deliver impactful solutions.

Tools and skills: Proficiency in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) are generally required, alongside strong mathematical and statistical skills.

Good fit for: Individuals with a strong analytical background, a passion for problem-solving, and the ability to translate theoretical concepts into practical, scalable solutions often thrive in this role.