Machine Learning Engineer

As a Machine Learning Engineer, you will have the opportunity to work on cutting-edge technologies and solve complex business problems using machine learning models. Your key responsibilities will include: - Designing, implementing, and deploying machine learning models to address challenging business issues. - Collaborating with cross-functional teams to seamlessly integrate models into production environments. - Optimizing models for superior performance, scalability, and reliability. - Preprocessing and cleaning large datasets to make them ready for modeling. - Performing feature engineering to enhance model accuracy and efficiency. - Implementing data augmentation techniques to enhance model generalization. - Evaluating model performance using suitable metrics and validation techniques. - Tuning hyperparameters and applying regularization methods to boost model performance. - Conducting error analysis and implementing strategies to enhance model accuracy. - Working closely with data scientists, software engineers, and product managers to define project requirements and deliver effective solutions. - Mentoring junior team members and sharing knowledge to create a collaborative learning environment. - Keeping up-to-date with the latest advancements in machine learning and artificial intelligence. - Experimenting with new algorithms, tools, and techniques to improve existing models and processes. In addition to the above responsibilities, the company values continuous learning and innovation, providing you with opportunities to expand your technical skills. You should have proficiency in programming languages such as Python, Java, or C++, experience with machine learning frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Keras, and familiarity with data processing tools and libraries such as Pandas, NumPy, and SQL. With at least 4 years of experience in machine learning engineering or a related role, along with a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, you will be well-equipped to excel in this role. Please note that this is a Full-time position with a Day shift schedule and the work location is in person.,