AI/ML Engineer – Freshers (2023),Mindfire Solutions

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Mindfire Solutions


About the Job FeaturedAs an AI/ML Engineer, you will be responsible for designing, validating, and integrating cutting-edge machine learning models and algorithms. Collaborate closely with cross-functional teams, including data scientists, to recognize and establish project objectives. Oversee data infrastructure maintenance, ensuring streamlined and scalable data operations. Stay updated with advancements in AI and propose their integration for operational enhancement. Effectively convey detailed data insights to non-technical stakeholders. Uphold stringent data privacy and security protocols. Engage in the full lifecycle of AI projects, spanning from ideation through deployment and continuous upkeep.Core ResponsibilitiesDevelop, validate, and implement machine learning models and algorithms.Collaborate with data scientists and other stakeholders to understand and define project goals.Maintain data infrastructure and ensure scalability and efficiency of data-related operations.Stay abreast of the latest developments in the field of AI/Client and recommend ways to implement them in our operations.Communicate complex data findings in a clear and understandable manner to non-technical stakeholders.Adhere to data privacy and security guidelines.Participate in the entire AI project lifecycle, from concept to deployment and maintenance.Required SkillsStrong foundation in machine learning concepts, algorithms, and data structures.Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).Proficiency in Python development in a Linux environment and using standard development tools.Basic understanding of data manipulation and analysis tools (e.g., Pandas, NumPy).Basic understanding of Computer Vision libraries like OpenCV.Excellent problem-solving skills and analytical thinking.Strong communication and teamwork skills.Eagerness to learn and adapt to new technologies and methodologies.Good to have knowledge on building ML Models using any of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs)Good to have knowledge on mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, bandwidth, and compute.Good to have knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud.CompensationQualificationsBachelor’s or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field.Proven hands-on experience/interest in AI/ML