JD_AI/ML Senior Engineer

About the Role

We are seeking a highly skilled and experienced AI/ML Engineer to join our dynamic team at Medibuddy dedicated to improving healthcare services experience. In this role, you will be instrumental in designing, developing, and deploying cutting-edge artificial intelligence and machine learning solutions that directly impact patient care and operational efficiency. You will leverage your expertise in cloud platforms, large language models, and robust MLOps practices to build scalable and observable AI systems. This position requires a strong advocate for best practices and a mentor who can guide junior engineers, fostering a culture of technical excellence and continuous improvement within the healthcare domain.

Responsibilities

• Champion and advocate for AI/ML best practices, including model governance, ethical AI, data privacy, and responsible AI development.

• Design, develop, and implement end-to-end AI/ML solutions, from data ingestion and model training to deployment and monitoring.

• Work extensively with Large Language Models (LLMs), including fine-tuning, prompt engineering, and integration into various applications.

• Implement comprehensive observability strategies for AI/ML systems, including logging, monitoring, alerting, and performance tracking to ensure system health and model efficacy.

• Architect and implement solutions for streaming existing software systems into AI/ML pipelines for real-time inference and data processing.

• Provide technical guidance, mentorship, and support to junior AI/ML engineers, helping them grow their skills and contribute effectively to the team.

• Collaborate closely with DevOps, software engineers, and product managers to translate business requirements into technical solutions.

• Conduct research and stay up-to-date with the latest advancements in AI/ML, cloud technologies, and industry trends.

• Familiarity with AWS cloud services to build, deploy, and manage scalable machine learning infrastructure and applications.

• Familiarity with developing and maintaining robust MLOps pipelines for continuous integration, continuous delivery (CI/CD), and automated model deployment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.

• 5+ years of professional experience in AI/ML engineering or a similar role.

• Strong proficiency in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

• Demonstrated experience working with Large Language Models (LLMs) and their applications.

• Hands-on experience with MLOps tools and practices, including CI/CD, version control (Git), and model monitoring.

• Expertise in setting up and maintaining observability for AI/ML systems (e.g., Prometheus, Grafana, ELK stack).

• Proven experience with AWS cloud services (e.g., Sagemaker, EC2, S3, Lambda, EKS) for deploying and managing ML workloads.

• Experience with real-time data streaming technologies (e.g., Kafka, Kinesis) and integrating them with ML pipelines.

• Excellent communication and interpersonal skills, with a proven ability to advocate for best practices and mentor junior team members.

• Strong problem-solving abilities and a keen attention to detail.