AI Consultant

7 days ago

Budapest, Hungary Avenga Full time

As a specialized consultant, you will play a critical role in advising GenAI solutions design, implementation, and productization. Your responsibilities will include providing expert guidance to ensure efficient and scalable deployment, seamless integration with existing systems, continuous monitoring and improvement of AI models, addressing biases, and upholding ethical AI practices in accordance with best practices of MLOps. Additionally, your innovative mindset will be essential in customizing and integrating models to meet specific organizational needs. If you are passionate about leveraging AI to drive impactful and ethical innovation, this consulting role provides the opportunity to join a team dedicated to pushing the boundaries of AI technology in the pharmaceutical industry.


  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
  • Proficiency in programming languages such as Python or R.
  • Experience with machine learning integration frameworks like Langchain, Llamaindex, or similar.
  • Strong understanding of MLOps principles, including CI/CD, version control, and automated testing.
  • Familiarity with cloud platforms such as AWS, GCP, or Azure and their portfolio of MLOps tools: SageMaker, Vertex AI, Azure ML Studio, etc.
  • Proven experience in deploying and managing machine learning models in production environments.
  • Hands-on experience in Vector Databases.
  • Track record of working in complex consulting engagements.delivering enterprise solutions.
  • Commitment to ethical AI practices and addressing biases
  • Hands-on experience with GenAI technologies and applications is a plus.
  • Strong background in data engineering and pipeline development.
  • Excellent problem-solving abilities and attention to detail.
  • Strong communication and collaboration skills.
  • Ability to work independently and as part of a team.
  • Experience with Kubernetes and containerization.
  • Knowledge of data governance and compliance standards.

As a specialized consultant, you will play a critical role in advising GenAI solutions design, implementation, and productization. Your responsibilities will include providing expert guidance to ensure efficient and scalable deployment, seamless integration with existing systems, continuous monitoring and improvement of AI models, addressing biases, and upholding ethical AI practices in accordance with best practices of MLOps. Additionally, your innovative mindset will be essential in customizing and integrating models to meet specific organizational needs. If you are passionate about leveraging AI to drive impactful and ethical innovation, this consulting role provides the opportunity to join a team dedicated to pushing the boundaries of AI technology in the pharmaceutical industry.

,[Implement and fine-tune GenAI models and pipelines., Deploy and manage machine learning models in production environments using MLOps best practices., Monitor and maintain the health, performance, and accuracy of deployed models., Ensure efficient and scalable deployment, and optimize resource usage., Evaluate the performance of large language models in the context of a specific domain., Work closely with data scientists, software engineers, and business stakeholders to understand requirements and deliver solutions., Communicate technical concepts and project status effectively to non-technical stakeholders., Seamlessly integrate GenAI models with existing systems and workflows., Engage in long and short term consulting projects, ranging from a few hours to months. That can be focused on different deliverables from simple PoCs to production grade solutions., Develop and maintain scalable and efficient MLOps infrastructure, including CI/CD pipelines, version control, and automated testing., Manage cloud-based infrastructure and resources for model training and deployment., Stay current with the latest developments in MLOps and GenAI technologies., Identify and implement best practices for model deployment, testing, and monitoring., Conduct post-deployment analysis and provide recommendations for solution improvements., Ensure all models and data pipelines comply with relevant regulatory requirements and data security standards., Implement robust security measures to protect sensitive data and intellectual property., Address biases and uphold ethical AI practices.] Requirements: Python, Machine Learning, MLOps, AWS, Data engineering, Kubernetes Additionally: Sport subscription, Training budget, Private healthcare, International projects.

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