Data Scientist - Machine Learning and AI GenAI Focus

As a Machine Learning Engineer at our company, you will be responsible for designing, developing, and deploying machine learning models to solve real-world business challenges. Your key responsibilities will include: - Working on the end-to-end machine learning lifecycle, which involves data preprocessing, model building, evaluation, deployment, and monitoring. - Implementing and managing MLOps pipelines to create scalable and reproducible workflows. - Utilizing tools like MLflow for experiment tracking, model versioning, and lifecycle management. - Developing and integrating Generative AI (GenAI) solutions such as LLM-based applications. - Collaborating with cross-functional teams including engineering, product, and business to translate requirements into AI solutions. - Optimizing model performance and ensuring production stability. - Staying updated with the latest advancements in AI, machine learning, and Generative AI ecosystems. To qualify for this role, you should have: - 4 years of experience in Data Science and Machine Learning. - Strong programming skills in Python. - Hands-on experience with various ML modeling techniques including supervised, unsupervised, and NLP. - A solid understanding of MLOps practices and tools. - Experience with MLflow or similar model lifecycle tools. - Practical experience in Generative AI (GenAI), including working with LLMs. - Familiarity with libraries and frameworks such as Scikit-learn, TensorFlow, and PyTorch. - Strong understanding of data structures, algorithms, and statistics. - Experience with cloud platforms like AWS, GCP, or Azure is a plus. Join our team and be part of cutting-edge projects that leverage machine learning to drive business success! As a Machine Learning Engineer at our company, you will be responsible for designing, developing, and deploying machine learning models to solve real-world business challenges. Your key responsibilities will include: - Working on the end-to-end machine learning lifecycle, which involves data preprocessing, model building, evaluation, deployment, and monitoring. - Implementing and managing MLOps pipelines to create scalable and reproducible workflows. - Utilizing tools like MLflow for experiment tracking, model versioning, and lifecycle management. - Developing and integrating Generative AI (GenAI) solutions such as LLM-based applications. - Collaborating with cross-functional teams including engineering, product, and business to translate requirements into AI solutions. - Optimizing model performance and ensuring production stability. - Staying updated with the latest advancements in AI, machine learning, and Generative AI ecosystems. To qualify for this role, you should have: - 4 years of experience in Data Science and Machine Learning. - Strong programming skills in Python. - Hands-on experience with various ML modeling techniques including supervised, unsupervised, and NLP. - A solid understanding of MLOps practices and tools. - Experience with MLflow or similar model lifecycle tools. - Practical experience in Generative AI (GenAI), including working with LLMs. - Familiarity with libraries and frameworks such as Scikit-learn, TensorFlow, and PyTorch. - Strong understanding of data structures, algorithms, and statistics. - Experience with cloud platforms like AWS, GCP, or Azure is a plus. Join our team and be part of cutting-edge projects that leverage machine learning to drive business success!