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 
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