Senior AI Engineer

• iCliniq is a pioneering global healthcare technology company committed to democratizing
• access to world class medical care. Our mission is to leverage cutting edge technology to
• ensure everyone, regardless of location, has access to top tier healthcare services. By
• integrating innovative AI solutions and telemedicine, we bridge the gap between patients and
• healthcare professionals, providing seamless and efficient medical care worldwide.
• We are currently seeking talented and passionate engineers to join our dynamic team with a
• culture of collaboration and continuous learning. If you are driven by innovation and eager to
• make a significant impact in the healthcare industry, we would love to hear from you. Please
• send your resume to [HIDDEN TEXT] . We look forward to connecting with you.

Role: Senior AI Engineer

Experience: 4-7 years

Work location: Onsite

iCliniqs AI Engineer core responsibilities:

1. Conceptualizing and Designing AI Solutions:

• ? Identifying AI Opportunities: You will work closely with business stakeholders to
• understand their challenges and identify areas where AI can provide significant
• advantages. This involves analyzing data, processes and workflows to pinpoint
• opportunities for automation, optimization and prediction.
• ? Solution Architecting: Once an opportunity is identified, you will design the
• technical architecture of the AI solution. This involves selecting appropriate
• machine learning models, outlining data pipelines and defining the integration
• points with existing systems.
• 2. Building and Training AI Models:
• ? Data Acquisition and Engineering: You will collaborate with data engineers to
• acquire, clean and prepare datasets for training machine learning models. This
• may involve data wrangling, feature engineering and ensuring data security and
• privacy.
• ? Model Development and Training: You will develop and train models on the
• prepared data. This involves choosing the right algorithms, hyperparameter
• tuning and iteratively improving the models performance through rigorous testing
• and evaluation.
• 3. Deployment and Management:
• ? Model Integration and Deployment: You will ensure smooth integration, handle
• infrastructure considerations and monitor the performance of deployed models.
• ? Performance Monitoring and Optimization: You will also continuously monitor the
• performance of AI models, identify potential biases or drifts and perform
• necessary optimizations to maintain accuracy and efficiency over time.
• 4. Collaboration and Communication:
• ? Cross Functional Collaboration: You will collaborate with data scientists, software
• engineers and product managers throughout the development lifecycle. Effective
• communication and knowledge sharing are essential for a successful outcome.
• ? Stakeholder Management: You are expected to present findings, explain
• technical concepts in clear language and manage expectations throughout the
• tenure.
• ? Documentation and Reporting: In addition to presenting findings and managing
• expectations, you are required to document data sources, model architectures,
• training procedures, evaluation metrics and deployment processes.
• 5. Regulatory Compliance and Ethical Considerations:
• ? Regulatory Compliance: Solutions you define may need to comply with various
• regulatory standards and guidelines. Responsibilities related to ensuring
• regulatory compliance, such as data protection laws (e.g., GDPR), industry
• specific regulations (e.g., healthcare regulations) and ethical guidelines (e.g.,
• IEEE Ethically Aligned Design..
• ? Ethical Considerations: You are also required to keep in mind issues such as bias
• mitigation, fairness, transparency and privacy protection in AI systems that you
• build.
• 6. Continuous Learning:
• ? Staying Current with AI Trends: You are responsible for staying up to date with
• the latest advancements in algorithms, frameworks and ethical considerations
• surrounding AI.