Senior Machine Learning Engineer

As a Machine Learning Engineer at PrashTech Solutions, you will play a crucial role in optimizing machine learning systems to enhance the accuracy of AI software's predictive automation capabilities. Your responsibilities will include consulting with managers to define machine learning objectives, designing machine learning systems and AI software for predictive automation, and applying appropriate ML algorithms and tools to transform data science prototypes. You will ensure accurate user recommendations, auto-tag images, convert text-to-speech, develop and deploy machine learning models for various applications, and build AI-driven chatbots using frameworks like Rasa, Dialogflow, or GPT-based models. Additionally, you will work with NLP techniques such as text classification, sentiment analysis, and entity recognition, deploy models on cloud platforms, and implement MLOps best practices. Collaboration with data engineers for preprocessing, cleaning, and analyzing large datasets will be essential, along with continuous monitoring and improvement of model performance. Lastly, you will develop and integrate APIs for seamless communication between ML models and applications, ensure security, scalability, reliability of AI-driven solutions, and stay updated with the latest advancements in machine learning and AI to keep solutions cutting-edge. **Key Responsibilities:** - Consulting with managers to determine and refine machine learning objectives. - Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. - Transforming data science prototypes and applying appropriate ML algorithms and tools. - Ensuring that algorithms generate accurate user recommendations. - Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions. - Design, develop, and deploy Machine Learning models for various applications, including chatbots and NLP solutions. - Build and optimize AI-driven chatbots using frameworks like Rasa, Dialogflow, or GPT-based models. - Work with Natural Language Processing (NLP) techniques such as text classification, sentiment analysis, and entity recognition. - Train, fine-tune, and optimize deep learning and machine learning models for production environments. - Deploy models on cloud platforms (AWS, GCP, Azure) and implement MLOps best practices. - Collaborate with data engineers to preprocess, clean, and analyze large datasets for model training. - Continuously monitor and improve the performance, accuracy, and efficiency of deployed models. - Develop and integrate APIs for seamless communication between ML models and applications. - Ensure the security, scalability, and reliability of AI-driven solutions. - Stay up to date with the latest machine learning and AI advancements to keep solutions cutting-edge. **Qualifications Required:** - 2-4+ years of experience in Machine Learning, AI, or Data Science. - Strong expertise in chatbot development using Rasa, Dialogflow, or OpenAI's GPT models. - Experience in building and deploying Machine Learning models for real-world applications. - Hands-on experience with Natural Language Processing (NLP) techniques and frameworks. - Strong understanding of model deployment using Docker, Kubernetes, Flask, or FastAPI. - Experience working with cloud platforms (AWS, GCP, Azure) for ML model deployment. - Proficiency in SQL and NoSQL databases for managing structured and unstructured data. - Knowledge of MLOps best practices for automating ML pipelines. - Familiarity with version control systems (Git, GitHub, GitLab). - Strong analytical, problem-solving, and debugging skills.,