Machine Learning Engineer

Job Description

Machine Learning Engineers (Hands on skills on Python) 3-4 years of experience in machine learning in Python , with a strong understanding of conversational AI, natural language processing (NLP), and familiarity with OpenAI's models (Llama 2, Gemini, Aphrodite). Developing and fine-tuning the AI model to capture, analyze calls and provide insights. Specializing in domain-specific (e.g., agriculture, Mistral AI) and general use case generation and optimization. Roles and Responsibilities of a Machine Learning Engineer To research, modify, and apply data science and data analytics prototypes. To create and construct methods and plans for machine learning. Employing test findings to do statistical analysis and improve models. To search internet for training datasets that are readily available. ML systems and models should be trained and retrained as necessary. To improve and broaden current ML frameworks and libraries. To create machine learning applications in accordance with client or customer needs. To investigate, test, and put into practice appropriate ML tools and algorithms. To evaluate the application cases and problem-solving potential of ML algorithms and rank them according to success likelihood. To better comprehend data through exploration and visualization, as well as to spot discrepancies in data distribution that might affect a model\u2019s effectiveness when used in practical situation Knowledge of data science. Languages for coding and programming, such as Python , Java, C++, C, R, and JavaScript. Practical understanding of ML frameworks. Practical familiarity with ML libraries and packages. Recognize software architecture, data modelling, and data structures. Understanding of computer architecture.