AI Engineer

As an AI Engineer, your primary responsibility will be to architect, develop, and deploy advanced AI solutions that incorporate Machine Learning, Generative AI, NLP, and LLMs. It is crucial to stay updated on the latest AI advancements, actively researching and integrating emerging trends and technologies such as LLMOps, Large Model Deployments, LLM Security, and Vector Databases. Your role will also involve streamlining data modeling processes to automate tasks, enhance data preparation, and facilitate data exploration for optimizing business outcomes. Collaboration with cross-functional teams, including business units, accounts teams, researchers, and engineers, will be essential to translate business requirements into actionable AI solutions. You must exhibit expertise in responsible AI practices, ensuring fairness, transparency, and interpretability in all models. Identifying and mitigating potential risks related to AI and LLM development and deployment, while emphasizing data trust and security, will also be part of your responsibilities. Moreover, you will contribute to the professional development of the AI team by mentoring engineers, fostering knowledge sharing, and promoting a culture of continuous learning. This role is based in a lab environment and requires hands-on, fast-paced, and high-intensity work. The ideal candidate should be proactive, adaptable, and comfortable working in a dynamic and demanding setting. To qualify for this position, you should have a minimum of 2 years of hands-on experience in developing and deploying AI solutions, with a proven track record of success. A Master's degree in Computer Science, Artificial Intelligence, or a related field (or equivalent experience) is required. Proficiency in Machine Learning, NLP, Generative AI, and LLMs, including their architectures, algorithms, and training methodologies, is essential. Additionally, you should have an understanding of LLMOps principles, Prompt Engineering, In-Context Training, LangChain, and Reinforcement Learning. Familiarity with best practices for large model deployment, monitoring, management, and scalability is crucial. Experience with Azure Cloud services, strong communication, collaboration, problem-solving abilities, and a commitment to ethical AI practices and security standards are also necessary. Proficiency in deep learning frameworks and languages such as Azure ML platform, Python, PyTorch, etc., along with hands-on experience with ML frameworks, libraries, and third-party ML models, is expected. Expertise in building solutions using AI/ML/DL open-source tools and libraries, strong analytical and problem-solving skills, the ability to write optimized and clear code, and address complex technical challenges effectively are important qualities for this role. Being self-motivated, a fast learner, with a proactive approach to learning new technologies, proficiency in data analysis and troubleshooting skills, and experience in building AI/ML/DL solutions for NLP/text applications, with familiarity in reinforcement learning being advantageous, are also required. A minimum of 2 years of experience on AI/ML/DL projects, with specialization or certification in Artificial Intelligence being a plus, and good knowledge of Azure AI/Cognitive Services tools are additional qualifications for this position.,