GenAI Engineer

Responsibilities: 

•   Develop and deploy machine learning, deep learning, and generative AI models

•   Utilize Python and frameworks like TensorFlow or PyTorch

•   Work with vector embeddings and perform prompt engineering

•   Implement AI solutions on Azure

•   Apply NLP techniques using BERT, GPT, or Transformer models

•   Ensure AI models adhere to trusted AI practices

•   Collaborate with software engineering and operations teams

•   Translate business requirements into technical solutions

Requirements:

•   Minimum 5 years of experience in Data Science and Machine Learning

•   In-depth knowledge of machine learning, deep learning, and generative AI techniques

•   Knowledge and experience in Generative AI

•   Proficiency in Python programming language, and frameworks like TensorFlow or PyTorch

•   Ability to work with vector embeddings and perform prompt engineering

•   Experience with Azure

•   Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models

•   Expertise in data engineering, including data curation, cleaning, and preprocessing

•   Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems

•   Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models

•   Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions

•   Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels

•   Track record of driving innovation and staying updated with the latest AI research and advancements

•   Bachelor's or Master's degree in Computer Science, Engineering, or a related field

•   Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems

•   Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI

•   Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines

•   Implement monitoring and logging tools to ensure AI model performance and reliability

•   Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment

•   Experience with ElasticDB or similar for data storage and retrieval

•   Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models

Our offer:

•   Workplace: 100% remote 

•   MultiSport Plus

•   Group insurance

•   Medicover Premium

•   e-learning platform