Machine Learning Engineer

SKMCH&RC is seeking a highly skilled Machine Learning Engineer to join our innovative team. This role is pivotal in developing cutting-edge machine learning models that drive decision-making processes and enhance operational efficiency. The ideal candidate has robust programming skills, a solid foundation in probability and statistics, and experience with data modeling. You will work primarily with various machine learning frameworks like TensorFlow and PyTorch, and utilize your proficiency in Python to design, build, and maintain predictive models. As a Machine Learning Engineer, you will analyze large datasets, evaluate model performance, and iteratively refine algorithms to achieve optimal results. Although you will not manage a team, collaboration with data scientists, software engineers, and other stakeholders is essential to delivering the best solutions for our projects. You'll play a critical role in ensuring that machine learning systems are robust, scalable, and integrated seamlessly with business processes.
Responsibilities

Design and implement machine learning algorithms and models to solve complex business problems.
Analyze and preprocess large datasets to extract relevant features for model training.
Evaluate and optimize existing models for performance and accuracy, ensuring they meet project requirements.
Collaborate with cross-functional teams to gather and define project requirements and scope.
Utilize programming languages, particularly Python, to develop scalable solutions for machine learning applications.
Leverage machine learning frameworks such as TensorFlow and PyTorch for implementing deep learning models.
Communicate findings and insights to non-technical stakeholders, translating complex concepts into understandable terms.
Stay updated with the latest trends and advancements in machine learning and artificial intelligence.
Document processes and methodologies in detail to create a comprehensive knowledge base for future reference.
Participate in code reviews and contribute to the continuous improvement of development processes.