Artificial Intelligence Specialist - Deep/Machine Learning

Job Title: AI Specialist Location: India (Preferred Bangalore, Chennai, Noida, Hyderabad) Job Type: Full-time Mandatory Skills : GenAI Architect Job Description PhD or Master's degree in Computer Science, Artificial Intelligence, or a related field. Experience : - Around 10 years of professional experience in roles such as Data Scientist or similar positions. - Proven experience in training large deep learning models and handling real-world data. - Experience in leading teams and managing complex projects in dynamic environments. Technical Expertise : - Strong expertise in Foundation Models and Transformer Models. - Deep understanding of Machine Learning algorithms, especially their applications to structured data in business contexts. - Comprehensive knowledge of the challenges and opportunities of applying Generative AI in a business environment. Preferred Skills : - Professional experience with Machine Learning on structured data in domains such as ERP or CRM. - Knowledge of privacy-preserving AI techniques is a plus. Leadership Skills : - Exceptional leadership capabilities with a demonstrated history of setting and achieving team goals, delegating responsibilities, and mentoring team members. - Strong interpersonal and organizational skills to effectively manage and communicate within large, diverse teams. - Proven ability to deliver results and manage high-stakes projects. Communication : - Excellent verbal and written communication skills to articulate complex AI solutions to diverse stakeholders. Technical Skills : - Expertise in architecting and deploying generative AI solutions, particularly in large-scale systems. - Strong experience working with large foundation models like GPT, BERT, T5, etc. , and fine-tuning them for specific applications. - Deep understanding of Transformer-based architectures, including BERT, GPT, and other variants. - Hands-on experience with popular frameworks such as TensorFlow, PyTorch, and Keras. - Expertise in training, fine-tuning, and optimizing large deep learning models using high-performance compute resources (GPUs/TPUs). - In-depth knowledge of various neural network architectures (CNN, RNN, LSTMs, GANs, etc. - Proficient in applying both supervised and unsupervised machine learning techniques to diverse data sets. - Expertise in model evaluation methods, including cross-validation, precision-recall, F1-score, ROC/AUC, etc. - Knowledge of applying reinforcement learning techniques for real-world problem-solving. - Familiarity with big data processing frameworks like Apache Spark, Hadoop, or similar platforms for large-scale data manipulation and preprocessing. - Skilled in handling noisy, missing, and unstructured data, and transforming it for AI model use. - Experience with distributed computing models for training large-scale machine learning models (ref:hirist.tech)

Location: in, IN

Posted Date: 12/22/2024