Job Role Machine Learning Engineer

Job Location Livonia, MI (Onsite)

Job Duration Full Time position with Caresoft

Responsibilities

Develop and deploy state-of-the-art machine learning models and algorithms for NLP and computer vision applications.
Conduct research and stay up-to-date with the latest advancements in NLP and computer vision to ensure our solutions are cutting-edge.
Collaborate with cross-functional teams including AI Research Tech Leads , software engineer(s), and product manager to understand business requirements and translate them into technical solutions.
Design and implement NLP models and techniques for text generation, information retrieval, sentiment analysis, named entity recognition, topic modeling, and machine translation.
Develop computer vision algorithms for tasks such as image classification, object detection, image segmentation, and visual recognition.
Perform data preprocessing, feature engineering, and model evaluation to ensure high-quality and accurate results.
Collaborate with data engineers (vendors) to build scalable and efficient data pipelines for training and testing.
Explore and implement advanced techniques in data augmentation, regularization, and model compression to improve performance and efficiency.
Deploy and maintain machine learning models in cloud platforms such as AWS ensuring scalability and reliability.
Conduct regular performance evaluations, identify bottlenecks, and implement optimization strategies to enhance model efficiency and accuracy.

Preferred Qualifications

Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field.
Strong background in machine learning, with expertise in NLP and computer vision.
Proficiency in programming languages such as Python, Java, or C++.
Experience: Minimum 3-5 years of experience as a Machine Learning Engineer, with significant exposure to NLP and computer vision projects. Proven track record of developing and deploying successful machine learning models.
Strong knowledge of machine learning frameworks and libraries, including TensorFlow, Keras, PyTorch, and scikit-learn.
Solid understanding of NLP techniques, including word embeddings, named entity recognition, sentiment analysis, and machine translation.
Extensive experience with computer vision algorithms and frameworks, including image classification, object detection, image segmentation, and deep learning models like CNNs and GANs.
Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
Experience with cloud platforms such as AWS/Azure for deploying and managing machine learning models.
Analytical mindset: Strong problem-solving skills, with the ability to analyze complex data and derive actionable insights. A solid understanding of statistical analysis and data visualization techniques.
Communication and collaboration: Excellent verbal and written communication skills. Proven ability to collaborate effectively with cross-functional teams, explain complex concepts to non-technical stakeholders, and contribute to a positive team environment.

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Machine Learning Engineer