Machine Learning Engineer

As a Machine Learning Engineer at Stylo, you will utilize your expertise to design and implement innovative machine learning algorithms that drive intelligent solutions. With a strong focus on problem-solving, you will work on predictive AI, leveraging techniques such as deep learning and traditional machine learning methods. Although you will not be managing a team, you will play an essential role in collaborating with cross-functional teams to develop machine learning models, ensuring they align with business objectives and technical requirements. Your hands-on experience with Generative AI, alongside your knowledge of model deployment and data engineering, will be crucial in creating prototypes and applications that effectively integrate machine learning into our operational framework. In this dynamic role, you will also contribute to the broader AI and data strategy of Stylo. Youll be expected to stay updated on industry trends and technologies that will impact the field of machine learning and AI. By actively contributing to the development of scalable AI solutions, you will help secure Stylo's position as a leader in leveraging technology for business growth. Ultimately, your passion for machine learning and proactive approach to problem-solving will shape the way we harness data and advanced algorithms to drive decision-making and innovation.

Responsibilities

Design and implement machine learning algorithms tailored to solve complex business problems.
Develop and optimize predictive AI models using deep learning and traditional machine learning techniques.
Integrate Generative AI techniques into existing systems and applications to enhance functionality.
Collaborate with cross-functional teams to define requirements and create solutions that align with project goals.
Deploy machine learning models using best practices in MLOps and monitor their performance for optimization.
Work with various data engineering tools and technologies to build, maintain, and improve data pipelines.
Create web-based prototypes and applications to facilitate user interaction with machine learning models.
Conduct research to stay current on emerging technologies and methodologies in machine learning and AI.
Utilize frameworks such as Scikit-learn, Pandas, and NumPy for data analysis and manipulation.
Assist in the documentation of models and processes to ensure clarity and reproducibility of results.