Machine Learning Engineer

As a Machine Learning Engineer, your primary responsibility will be to design, develop, and deploy machine learning models that power various applications such as predictive analytics, natural language processing, computer vision, recommendation systems, and more. You will closely collaborate with data scientists, software engineers, and product teams to create scalable and high-performance AI solutions. Having a solid foundation in machine learning algorithms, data processing, and software development is essential for this role. You should be capable of taking charge of the complete machine learning lifecycle, starting from data collection and model training to deployment and monitoring. Your key responsibilities will include designing and implementing machine learning models for different applications, working with large datasets for data preparation and processing, training and optimizing models using modern frameworks, deploying models into production environments, monitoring model performance and scalability, collaborating with cross-functional teams, and staying updated on the latest trends in machine learning and AI for driving innovation within the organization. To qualify for this position, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field. While a PhD is advantageous, it is not mandatory. You are expected to have 0-1 years of experience in machine learning, data science, or a related technical role, with a proven track record of building and deploying machine learning models in production environments. Proficiency in Python (or other programming languages), knowledge of machine learning frameworks like TensorFlow and PyTorch, familiarity with deep learning techniques, experience with cloud platforms for model deployment, and expertise in data processing tools are essential technical skills required. In addition to technical skills, possessing strong problem-solving abilities, excellent communication and collaboration skills, the capacity to work independently in a fast-paced environment, attention to detail, and a passion for learning and innovation are crucial soft skills for success in this role. This is a full-time position with a day shift schedule, and the work location is in person.,